keyword stringlengths 4 52 | weight float64 0 1 | embedding stringlengths 15.8k 16k |
|---|---|---|
q learning algorithm sarsa | 0.797172 | [-0.21925653517246246, 0.22625184059143066, -0.6194822192192078, 0.1517924964427948, -1.014527678489685, -0.23606646060943604, 0.07562774419784546, -0.17007888853549957, -0.47865286469459534, 1.5347336530685425, -0.3341544568538666, -0.6057146787643433, -0.7270795106887817, -0.9297128915786743, -0.4160909056663513, -1.... |
q learning algorithm | 0.797172 | [-0.5829341411590576, 0.1411595493555069, -0.6153193116188049, -0.008518898859620094, -0.6052941083908081, -0.37940773367881775, 0.17745140194892883, -0.060634881258010864, -0.6400474309921265, 1.8080472946166992, -0.39505481719970703, -0.6007633209228516, -0.44205865263938904, -1.0563637018203735, -0.3357960879802704,... |
simple q learning algorithm | 0.797172 | [-0.6917383670806885, 0.14113110303878784, -0.46668195724487305, 0.09768664836883545, -0.6915626525878906, -0.2725082039833069, 0.2787758409976959, 0.009411238133907318, -0.8261540532112122, 1.796829104423523, -0.42877867817878723, -0.6631459593772888, -0.30459341406822205, -0.9800440669059753, -0.4947162866592407, -0.... |
well known q learning algorithm | 0.797172 | [-0.5738764405250549, -0.022756988182663918, -0.564170241355896, 0.16569426655769348, -0.6684280633926392, -0.3954460918903351, 0.43712636828422546, 0.17895594239234924, -0.7722468972206116, 1.6630843877792358, -0.38027748465538025, -0.5154586434364319, -0.4079115092754364, -1.0641659498214722, -0.47603946924209595, -0... |
classical q learning algorithm | 0.797172 | [-0.4918861389160156, 0.07035550475120544, -0.5486962795257568, 0.15537558495998383, -0.839613676071167, -0.26356515288352966, 0.28313127160072327, -0.008815706707537174, -0.7876079082489014, 1.676141619682312, -0.5282296538352966, -0.5135226845741272, -0.28898075222969055, -1.0274914503097534, -0.4797774851322174, -0.... |
modified q learning algorithm | 0.797172 | [-0.48639175295829773, -0.011102910153567791, -0.4732376039028168, 0.08698949217796326, -0.7392642498016357, -0.28025928139686584, 0.059177737683057785, -0.19336014986038208, -0.8650474548339844, 1.8248947858810425, -0.45160913467407227, -0.4790457487106323, -0.4825246334075928, -1.0850801467895508, -0.3331942260265350... |
improved q learning algorithm | 0.797172 | [-0.5488619208335876, 0.02499733865261078, -0.47912541031837463, 0.1529998630285263, -0.7418124079704285, -0.2982904016971588, 0.02820473723113537, -0.22098569571971893, -0.8106778264045715, 1.8483587503433228, -0.39787378907203674, -0.515496551990509, -0.4352303445339203, -1.0351924896240234, -0.2080577164888382, -0.8... |
reinforcement learning algorithm | 0.797172 | [-0.5414112210273743, 0.2579386234283447, -0.5501532554626465, 0.21813401579856873, -0.15183067321777344, -0.4287993013858795, 0.746256947517395, -0.22351369261741638, -0.6070348024368286, 1.9042764902114868, -0.42307788133621216, -0.7177008986473083, -0.14046737551689148, -1.2446783781051636, -0.6329302191734314, -0.8... |
machine learning model | 0.796917 | [-0.058689944446086884, 0.09419900178909302, -0.8115586042404175, -0.5905469655990601, -0.15216366946697235, -0.318358838558197, 0.8307499885559082, -0.0007608175510540605, -0.19620701670646667, 0.7468282580375671, -0.10045929998159409, -1.0122278928756714, -0.25359171628952026, -1.2179028987884521, -0.4134854376316070... |
learning machine model | 0.796917 | [-0.044307734817266464, 0.37061843276023865, -0.8440128564834595, -0.8661373257637024, -0.42901402711868286, -0.18767425417900085, 0.7333200573921204, -0.14536598324775696, -0.0936628207564354, 0.7741268873214722, -0.18361198902130127, -0.7137983441352844, -0.11856056749820709, -1.251213788986206, -0.6456494331359863, ... |
named entity recognition ner | 0.794598 | [-0.5905296206474304, 0.29707634449005127, 0.0750906839966774, -0.44294413924217224, -1.0582427978515625, -0.9193376898765564, 0.14106105268001556, 0.1898592859506607, -1.5860223770141602, 1.8278199434280396, 0.6226590871810913, -0.536253035068512, 0.3692575991153717, -0.8055512309074402, -0.5166943669319153, 0.0388337... |
named entity recognition model | 0.794598 | [-0.7016409039497375, 0.17619337141513824, -0.46918973326683044, -0.74749755859375, -0.7663137316703796, -0.5001328587532043, 0.2995467483997345, -0.03359607234597206, -1.169473648071289, 1.6523008346557617, 0.6283208727836609, -0.5716472268104553, 0.3682609498500824, -1.0736565589904785, -0.4068240225315094, 0.0153733... |
named entity recognizers | 0.794598 | [-0.5452739596366882, 0.3053196668624878, -0.31802359223365784, -0.7640451788902283, -0.9840614795684814, -0.9382235407829285, 0.0676983892917633, 0.059898313134908676, -1.2062464952468872, 1.771551251411438, 0.39004385471343994, -0.6596020460128784, 0.31949833035469055, -0.8934919834136963, -0.6316762566566467, 0.1041... |
named entity recognizer | 0.794598 | [-0.6653068661689758, 0.11088903993368149, -0.15177269279956818, -0.7970239520072937, -0.992135226726532, -0.9459603428840637, 0.032808978110551834, 0.07122296839952469, -1.1358288526535034, 1.7662744522094727, 0.4086456298828125, -0.6798727512359619, 0.5258638262748718, -0.8432900309562683, -0.5988208055496216, 0.0924... |
supervised named entity recognition | 0.794598 | [-0.41570374369621277, 0.34909048676490784, -0.37941601872444153, -1.0008360147476196, -0.8915328979492188, -0.7622663974761963, 0.30025234818458557, 0.3102432191371918, -1.1873518228530884, 1.8962634801864624, 0.5174868106842041, -0.5552659630775452, 0.5359081625938416, -0.9452868103981018, -0.8127245903015137, -0.078... |
named entity recognition | 0.794598 | [-0.5802232027053833, 0.186200350522995, -0.15272650122642517, -0.9200384020805359, -0.9313623309135437, -0.8707379102706909, 0.09002768993377686, 0.16337242722511292, -1.2668607234954834, 1.887129545211792, 0.4964071214199066, -0.5620044469833374, 0.42074745893478394, -0.8692000508308411, -0.6034122705459595, -0.18831... |
named entity identification | 0.794598 | [-0.7357492446899414, 0.3536842167377472, -0.20925617218017578, -0.7407811284065247, -0.9149273633956909, -0.8893750309944153, 0.1327369213104248, 0.3086358904838562, -1.2901335954666138, 1.870875597000122, 0.6463557481765747, -0.5673590898513794, 0.2378838062286377, -0.9163252115249634, -0.40573033690452576, -0.047045... |
recognizing named entity | 0.794598 | [-0.5073553323745728, 0.3405965566635132, -0.19302378594875336, -0.9822206497192383, -0.8898221850395203, -1.1255029439926147, 0.11548874527215958, 0.13648566603660583, -0.8611661791801453, 1.6206108331680298, 0.6277817487716675, -0.4916616976261139, 0.44875383377075195, -1.0166237354278564, -0.6613581776618958, -0.082... |
natural language understanding | 0.794233 | [0.09035072475671768, 0.7739529609680176, -0.08713968843221664, -0.7921777367591858, -0.44010502099990845, -0.7558177709579468, 0.9802200198173523, 0.4751524329185486, 0.05599621683359146, 0.7437950968742371, 0.5583494901657104, -1.5087748765945435, 0.34908151626586914, -1.7115370035171509, -0.707752525806427, 0.186127... |
automatic data preprocessing | 0.793658 | [-0.07833496481180191, 0.012474732473492622, 0.08145947754383087, -1.1612398624420166, -0.6067647933959961, -0.21155431866645813, 0.24445565044879913, 1.3688726425170898, -1.0749244689941406, 0.6000773906707764, 0.2656872868537903, -0.5827611684799194, -0.14324843883514404, -1.7637735605239868, -0.4024074077606201, -1.... |
data data | 0.793658 | [-0.5739356279373169, 0.14532995223999023, -0.32919538021087646, -1.1851885318756104, -0.2174767702817917, -0.5188528895378113, 0.7380700707435608, 0.9619980454444885, -0.6607282757759094, 0.6149678230285645, 0.7778056859970093, -0.5949287414550781, -0.7572160363197327, -1.708106279373169, -0.376971572637558, -0.910380... |
data | 0.793658 | [-0.48059096932411194, 0.06857773661613464, -0.4015932083129883, -1.0629547834396362, -0.440279096364975, -0.7858497500419617, 0.8544595241546631, 0.6381860375404358, -0.8340678215026855, 0.7494271397590637, 0.6033845543861389, -0.8186923861503601, -0.5554251074790955, -1.431325078010559, -0.6379778981208801, -0.763068... |
data preprocessing | 0.793658 | [0.1849859654903412, 0.08599791675806046, -0.16334429383277893, -1.2053831815719604, -0.33730220794677734, -0.2998945116996765, 0.1321694254875183, 1.1841316223144531, -1.112181305885315, 0.4522142708301544, 0.3369813859462738, -0.8646270036697388, -0.3057783246040344, -1.7830250263214111, -0.49943873286247253, -0.9284... |
data free | 0.793658 | [-0.7731924057006836, 0.49756526947021484, -0.4669460356235504, -0.8443589210510254, -0.7567135691642761, -0.6900413632392883, 0.11648602038621902, 0.5785583257675171, -0.5792214870452881, 1.3121083974838257, 0.44543495774269104, -0.8928361535072327, -0.5252546668052673, -1.01029372215271, -0.33928778767585754, -0.5268... |
nlp task | 0.785995 | [-0.060547541826963425, 0.5388690829277039, -0.43763095140457153, -0.17345783114433289, -1.223542332649231, -1.4155702590942383, 0.5679600834846497, 0.4113858640193939, -0.6047645807266235, 1.8821849822998047, 0.9155518412590027, -0.6285155415534973, -0.001776540302671492, -0.6744993329048157, -1.2443716526031494, -0.5... |
processing nlp | 0.785995 | [0.17963896691799164, 0.6133086085319519, -0.11750557273626328, -0.43040236830711365, -1.0431052446365356, -1.3422330617904663, 0.5703042149543762, 0.5726001262664795, -0.5861153602600098, 1.452056884765625, 1.0897619724273682, -0.417296826839447, -0.11268868297338486, -1.2349129915237427, -1.0264886617660522, 0.064668... |
nlp progress | 0.785995 | [-0.12221000343561172, 0.6571246385574341, -0.8987168073654175, 0.04529011249542236, -1.4128201007843018, -1.2986173629760742, 0.34141841530799866, 0.16919702291488647, -0.646163821220398, 1.7977476119995117, 0.9696563482284546, -0.8202856183052063, -0.2761900722980499, -0.5008293986320496, -1.1363223791122437, -0.1447... |
nlp main task | 0.785995 | [-0.029670385643839836, 0.7675425410270691, -0.5323362946510315, -0.030411705374717712, -1.3537064790725708, -1.2747060060501099, 0.5593613982200623, 0.28737449645996094, -0.3855645954608917, 1.5814307928085327, 0.8590674996376038, -0.6689162850379944, 0.20438188314437866, -0.5550394654273987, -1.134844183921814, -0.48... |
nlp task verb | 0.785995 | [0.15648992359638214, 0.49536648392677307, -0.4419652223587036, -0.07192221283912659, -1.2846910953521729, -1.5063174962997437, 0.5075523257255554, 0.46733734011650085, -0.7239838242530823, 1.7181724309921265, 1.0231019258499146, -0.4552692174911499, -0.0806487575173378, -0.5390011668205261, -1.1168842315673828, -0.469... |
nlp task text | 0.785995 | [0.37120017409324646, 0.6937310099601746, -0.4123089611530304, -0.06674113124608994, -1.0726104974746704, -1.2583097219467163, 0.716511070728302, 0.6569020748138428, -0.5763248801231384, 1.4824481010437012, 1.166608452796936, -0.7436420917510986, -0.25760653614997864, -0.5409701466560364, -1.0392470359802246, -0.539502... |
multi task learning scheme | 0.784523 | [0.1856100708246231, -0.39885783195495605, 0.15233218669891357, -0.4099445044994354, -1.8839030265808105, -0.193197563290596, 0.347881555557251, -0.5643797516822815, -0.9782962799072266, 1.4177474975585938, -0.19400061666965485, 0.10722801089286804, 0.21186906099319458, -0.12092136591672897, -0.25744497776031494, -1.09... |
conventional multi task learning | 0.784523 | [0.06038320064544678, -0.3299329876899719, -0.09737657755613327, -0.47776398062705994, -1.8453413248062134, -0.0809173509478569, 0.39660322666168213, -0.601245105266571, -0.9997772574424744, 1.5035185813903809, -0.05221394822001457, -0.01174743752926588, 0.0588921420276165, 0.03491221368312836, -0.562932550907135, -0.9... |
multi task network | 0.784523 | [0.027231166139245033, -0.009376367554068565, -0.05942250415682793, -0.6200385093688965, -0.92542564868927, -0.14933229982852936, 0.03329765424132347, -0.7754631042480469, -0.681371808052063, 1.4491820335388184, -0.22362425923347473, -0.07749894261360168, -0.3364415466785431, -0.2984774708747864, -0.34154731035232544, ... |
efficient multi task learning | 0.784523 | [-0.009468808770179749, -0.6453724503517151, 0.036874573677778244, -0.4760400056838989, -2.111424446105957, -0.24179022014141083, 0.1546255350112915, -0.5730116963386536, -0.8703765869140625, 1.3336533308029175, -0.13215552270412445, 0.13809412717819214, 0.13015051186084747, 0.012438452802598476, -0.5590829849243164, -... |
efficient multi task network | 0.784523 | [-0.05235462263226509, -0.2433365136384964, -0.19053375720977783, -0.6345930695533752, -1.0262218713760376, -0.17039747536182404, -0.005658087786287069, -0.7488799691200256, -0.730942964553833, 1.4694637060165405, -0.061474889516830444, -0.02700735069811344, -0.11187200993299484, -0.2974430322647095, -0.431341528892517... |
hybrid multi task learning | 0.784523 | [0.015839949250221252, -0.5250721573829651, -0.04827286675572395, -0.3069063723087311, -2.0386950969696045, -0.12922990322113037, 0.3025679886341095, -0.5084096789360046, -0.7693784832954407, 1.3882466554641724, -0.2820570170879364, 0.14473697543144226, 0.04905230179429054, -0.04823794960975647, -0.2544289529323578, -1... |
sequential multi task learning | 0.784523 | [0.20027534663677216, -0.5236331820487976, 0.16244389116764069, -0.4234658479690552, -1.8436665534973145, -0.336382120847702, 0.44139325618743896, -0.5812811851501465, -0.9730001091957092, 1.2640626430511475, -0.19668757915496826, 0.025149943307042122, 0.2089449167251587, 0.1441245824098587, -0.5338043570518494, -0.885... |
multi task learning system | 0.784523 | [-0.023112580180168152, -0.4091605842113495, 0.17945629358291626, -0.5353257656097412, -1.724754810333252, -0.25059714913368225, 0.2292054444551468, -0.6391883492469788, -0.8444668650627136, 1.2958980798721313, -0.5061643719673157, 0.07693863660097122, 0.15061430633068085, -0.07917848974466324, -0.272068053483963, -1.0... |
multi task learning promise | 0.784523 | [0.0053532421588897705, -0.33248746395111084, -0.2260650247335434, -0.5783365368843079, -2.1314728260040283, -0.1124025508761406, 0.445862740278244, -0.6878767609596252, -0.45311811566352844, 1.2228626012802124, 0.13217006623744965, 0.2858680784702301, -0.16737012565135956, 0.0062219551764428616, -0.654606282711029, -1... |
shared multi task feature | 0.784523 | [-0.41285017132759094, -0.31271061301231384, 0.42705366015434265, -0.9801278710365295, -1.9153350591659546, -0.25442278385162354, 0.21908552944660187, -0.7553913593292236, -0.36312904953956604, 1.2067588567733765, 0.47825586795806885, 0.8118471503257751, -0.32350924611091614, -0.10823925584554672, -0.26172196865081787,... |
multi task network approach | 0.784523 | [0.15859825909137726, -0.08930204063653946, -0.0867634117603302, -0.8320187926292419, -0.8324080109596252, -0.06549414247274399, 0.06712508946657181, -0.5470036864280701, -0.6983596682548523, 1.3674815893173218, -0.10221162438392639, 0.023395320400595665, -0.693324863910675, -0.4166020452976227, -0.283755362033844, -0.... |
based multi task learning | 0.784523 | [0.07868701964616776, -0.39825353026390076, 0.05484390631318092, -0.5939307808876038, -2.091514825820923, 0.058045972138643265, 0.2444080114364624, -0.5754475593566895, -0.7922635674476624, 1.2455061674118042, -0.1656513214111328, 0.1400870680809021, 0.05435663089156151, 0.10441866517066956, -0.295114129781723, -0.9206... |
multi task neural network | 0.784523 | [0.15853922069072723, -0.5323056578636169, 0.17023150622844696, -0.591421902179718, -1.5753823518753052, -0.09364679455757141, 0.18722683191299438, -0.8491644263267517, -0.7969205379486084, 1.2061054706573486, -0.251501202583313, -0.03020765446126461, 0.0025452810805290937, -0.06470070034265518, -0.23920418322086334, -... |
multi task learning manner | 0.784523 | [-0.05767321586608887, -0.3935448229312897, 0.29130902886390686, -0.5918993353843689, -1.7547632455825806, -0.31223124265670776, 0.21696078777313232, -0.6705112457275391, -1.0628501176834106, 1.3195509910583496, -0.23854322731494904, 0.22014737129211426, 0.22656865417957306, -0.17595653235912323, -0.4236236810684204, -... |
incremental multi task learning | 0.784523 | [0.1177462562918663, -0.23477821052074432, 0.031551916152238846, -0.45409950613975525, -1.9531480073928833, -0.22117610275745392, 0.26503708958625793, -0.6927377581596375, -0.8656910061836243, 1.4265364408493042, -0.14596696197986603, 0.04076963663101196, 0.33411744236946106, 0.1645023077726364, -0.7303717136383057, -0... |
multi task | 0.784523 | [-0.14717966318130493, -0.5022334456443787, 0.030945567414164543, -0.6258532404899597, -1.9620349407196045, -0.3686487078666687, 0.2750478982925415, -0.5455138087272644, -1.0425589084625244, 1.3267407417297363, 0.04224926233291626, -0.05263552814722061, 0.04641728848218918, 0.18660137057304382, -0.37885984778404236, -0... |
multi task learning | 0.784523 | [0.040754981338977814, -0.38364464044570923, 0.17540886998176575, -0.5148763656616211, -2.0515384674072266, -0.27793270349502563, 0.28433939814567566, -0.6771684288978577, -0.8915563821792603, 1.2825047969818115, -0.19457551836967468, 0.13666167855262756, 0.06763484328985214, 0.13061068952083588, -0.483079195022583, -1... |
multi task learning network | 0.784523 | [0.09429534524679184, -0.3096100389957428, 0.10662546008825302, -0.4403747618198395, -1.5520535707473755, -0.14509814977645874, 0.21345888078212738, -0.6752167344093323, -0.7569074630737305, 1.310710072517395, -0.36040326952934265, 0.08815783262252808, -0.06452088803052902, -0.1258239895105362, -0.37087950110435486, -0... |
guided multi task learning | 0.784523 | [0.3370659649372101, 0.21467401087284088, 0.00917024165391922, -0.5445634126663208, -2.1966469287872314, -0.2484220415353775, 0.37171435356140137, -0.5985913872718811, -0.7901238799095154, 1.3009618520736694, 0.05641153082251549, -0.09194312244653702, -0.1072847843170166, 0.0077758305706083775, -0.5011398196220398, -1.... |
multi task learning dataset | 0.784523 | [0.11017138510942459, -0.2734377980232239, 0.019890744239091873, -0.7151150703430176, -1.7905468940734863, -0.3949327766895294, 0.19464045763015747, -0.4301196038722992, -0.9912946820259094, 1.4383755922317505, -0.16657774150371552, 0.2361772507429123, -0.06648638844490051, -0.09202779084444046, -0.3710545003414154, -0... |
multi task learning framework | 0.784523 | [0.027525214478373528, -0.41278210282325745, 0.21844147145748138, -0.5919065475463867, -1.8852437734603882, -0.23621635138988495, 0.413489431142807, -0.578091561794281, -0.876287043094635, 1.0992250442504883, -0.13362206518650055, 0.22965729236602783, 0.14884686470031738, -0.16966092586517334, -0.45711418986320496, -0.... |
multi task learning approach | 0.784523 | [0.07908812910318375, -0.32734671235084534, 0.12485132366418839, -0.5840351581573486, -2.021251916885376, -0.22821612656116486, 0.42715802788734436, -0.4514404535293579, -0.9536256790161133, 1.2103588581085205, -0.04422923922538757, 0.14333628118038177, 0.07408399134874344, -0.11119679361581802, -0.3638168275356293, -0... |
multi task learning model | 0.784523 | [-0.038592804223299026, -0.2623256742954254, -0.0035981088876724243, -0.5724592804908752, -1.7946252822875977, -0.08556535840034485, 0.4203549921512604, -0.6629621982574463, -0.8833293914794922, 1.0656040906906128, -0.06217768415808678, 0.13501040637493134, 0.1188715472817421, -0.0928155854344368, -0.4512076675891876, ... |
multi task learning problem | 0.784523 | [0.2674470841884613, -0.336978942155838, 0.24381740391254425, -0.4689595401287079, -2.0276594161987305, -0.24996070563793182, 0.19852475821971893, -0.6265977025032043, -0.8857696056365967, 1.4931020736694336, -0.3612110912799835, 0.2149709016084671, -0.027151254937052727, 0.010350607335567474, -0.4017117917537689, -1.1... |
multi task learning method | 0.784523 | [0.044243406504392624, -0.4860776960849762, 0.08605391532182693, -0.40828680992126465, -2.064772367477417, -0.23774830996990204, 0.42841434478759766, -0.678095281124115, -0.8066471219062805, 1.3532675504684448, -0.15874405205249786, 0.12681831419467926, 0.22111809253692627, -0.13609372079372406, -0.2219330221414566, -1... |
standard multi task learning | 0.784523 | [0.18291307985782623, -0.5007337927818298, 0.13954927027225494, -0.5347939133644104, -1.795304298400879, -0.16576655209064484, 0.45604273676872253, -0.5978397130966187, -0.9932268261909485, 1.4262746572494507, -0.14884166419506073, 0.10164159536361694, 0.16147680580615997, -0.03982703387737274, -0.5932961702346802, -1.... |
multi task learning paradigm | 0.784523 | [0.15508688986301422, -0.43745970726013184, 0.2682062089443207, -0.5119860768318176, -1.7514219284057617, -0.1361767053604126, 0.3820834457874298, -0.5897111892700195, -1.0238169431686401, 1.3442045450210571, -0.3675098717212677, 0.22627393901348114, -0.058877501636743546, -0.18521763384342194, -0.40892139077186584, -1... |
multi task training | 0.784523 | [-0.060877155512571335, -0.28377988934516907, 0.14502260088920593, -0.6837838888168335, -1.7209980487823486, -0.37682026624679565, 0.19004034996032715, -0.7055832147598267, -1.0427864789962769, 1.1665456295013428, -0.28702202439308167, -0.17061208188533783, 0.28262659907341003, 0.07730899751186371, -0.6723015308380127,... |
multi task learning issue | 0.784523 | [0.19192850589752197, -0.36728420853614807, 0.24521994590759277, -0.5083548426628113, -2.0454537868499756, -0.1676630973815918, 0.06489407271146774, -0.6094584465026855, -1.0491297245025635, 1.588962197303772, -0.2781252861022949, 0.22651581466197968, 0.09693566709756851, 0.12008222937583923, -0.45121490955352783, -0.9... |
joint multi task learning | 0.784523 | [-0.28637346625328064, -0.3693937063217163, 0.07044453918933868, -0.38748788833618164, -2.399049997329712, -0.20079071819782257, 0.4453350007534027, -0.7346019744873047, -0.895444929599762, 1.2046786546707153, 0.04752885922789574, 0.20432980358600616, 0.35965394973754883, 0.34755846858024597, -0.5806405544281006, -0.84... |
existing multi task learning | 0.784523 | [-0.024916386231780052, -0.4743218421936035, -0.105400450527668, -0.5024877786636353, -1.8026123046875, -0.23644952476024628, 0.4035426676273346, -0.5273891687393188, -0.8952023983001709, 1.1912561655044556, 0.026624927297234535, 0.04002334550023079, 0.2961307466030121, 0.0015330687165260315, -0.4573420286178589, -0.87... |
generic multi task learning | 0.784523 | [0.12494492530822754, -0.37203240394592285, 0.14730612933635712, -0.560568630695343, -2.0228793621063232, -0.30389705300331116, 0.3070921003818512, -0.67339688539505, -0.8864736557006836, 1.2295726537704468, -0.2760830223560333, 0.16647633910179138, 0.21233534812927246, 0.21038372814655304, -0.5634229779243469, -1.1378... |
utilizing multi task learning | 0.784523 | [-0.021957842633128166, -0.6148639917373657, -0.3832998275756836, -0.4791250228881836, -1.8865528106689453, -0.1877182275056839, 0.10653436928987503, -0.6352757215499878, -0.704937756061554, 1.4352703094482422, -0.004884272813796997, 0.02066953293979168, 0.18623030185699463, -0.0562882237136364, -0.4003433287143707, -0... |
unified multi task learning | 0.784523 | [-0.23299682140350342, -0.633355975151062, 0.11899879574775696, -0.44515395164489746, -2.0544214248657227, -0.1746242493391037, 0.14363357424736023, -0.8119474053382874, -0.9158535599708557, 1.4038208723068237, -0.1231708824634552, 0.0035378020256757736, 0.2935543954372406, 0.12516699731349945, -0.4876572787761688, -0.... |
single multi task network | 0.784523 | [0.223706915974617, 0.19585148990154266, -0.05199437215924263, -0.3851269781589508, -0.7581836581230164, -0.3890398442745209, 0.24223321676254272, -1.0320038795471191, -0.6522591710090637, 1.425614833831787, -0.4579054117202759, -0.252362459897995, -0.08535780757665634, -0.1651972085237503, -0.6024487614631653, -0.9613... |
automated multi task learning | 0.784523 | [0.09773492813110352, -0.17849315702915192, 0.1707262396812439, -0.5475003123283386, -2.2339303493499756, -0.4206182062625885, 0.3163839280605316, -0.4200357496738434, -0.6908766627311707, 1.3116339445114136, -0.15681692957878113, 0.0931043028831482, 0.04927471652626991, 0.26941725611686707, -0.4815733730792999, -0.936... |
multi task learning challenge | 0.784523 | [0.06093331798911095, -0.17232155799865723, 0.14779545366764069, -0.4286295473575592, -1.9316133260726929, -0.3604254722595215, 0.48502612113952637, -0.6226035952568054, -0.9126439690589905, 1.203220248222351, -0.10791043192148209, 0.1523643285036087, 0.2798563241958618, 0.14644119143486023, -0.6629694104194641, -0.871... |
shared task | 0.784523 | [-0.22906941175460815, 0.17177611589431763, 0.37657350301742554, -0.6405799388885498, -1.633643388748169, -0.563669741153717, 0.3028605282306671, -0.48688095808029175, -0.583386242389679, 1.1685646772384644, 0.33840876817703247, -0.09242737293243408, -0.11432823538780212, -0.13215422630310059, -0.25804340839385986, -1.... |
multi task machine learning | 0.784523 | [0.14405106008052826, -0.6033322811126709, 0.13717830181121826, -0.6632218956947327, -2.012599229812622, -0.32581761479377747, 0.40980157256126404, -0.4856739044189453, -0.7206969857215881, 1.3240724802017212, -0.11667229980230331, -0.014521158300340176, 0.19410927593708038, 0.0019522774964571, -0.3646251857280731, -0.... |
structured multi task learning | 0.784523 | [0.411533385515213, 0.09014004468917847, 0.18576359748840332, -0.692112386226654, -2.1373612880706787, -0.23328621685504913, 0.11076200008392334, -0.5977912545204163, -0.6920145153999329, 1.3853851556777954, 0.16766208410263062, 0.026553824543952942, 0.0628684014081955, 0.27737078070640564, -0.6451734304428101, -0.8992... |
natural language generation | 0.782854 | [0.274368554353714, 1.4037582874298096, 0.1067032590508461, -0.15643224120140076, -0.8856796026229858, -0.6674315929412842, 1.357102394104004, -0.21054235100746155, 0.1411595344543457, 1.8530584573745728, 0.5437662601470947, -0.6732213497161865, 0.8547919392585754, -1.7465999126434326, -0.833386242389679, 0.21648769080... |
natural language generating | 0.782854 | [0.3162378966808319, 1.253027081489563, 0.11138339340686798, -0.20510482788085938, -0.9629982113838196, -0.7596774101257324, 1.185506820678711, -0.03528161719441414, 0.12435223907232285, 1.5060012340545654, 0.6813265085220337, -0.898550808429718, 0.7853798270225525, -1.632309913635254, -1.044817566871643, 0.21982474625... |
stochastic gradient descent | 0.781852 | [-0.6076151132583618, -0.3797922730445862, -0.17491988837718964, -0.8790656924247742, -0.8499003648757935, -0.2933505177497864, -0.022497499361634254, -0.42247891426086426, -1.187208652496338, 1.453810691833496, -0.11174853891134262, -1.0250282287597656, 0.47448626160621643, -0.8089076280593872, -0.5751805305480957, -0... |
quasi stochastic gradient descent | 0.781852 | [-0.5198354721069336, -0.2754571735858917, -0.08189940452575684, -0.9908397793769836, -1.1454761028289795, -0.0625530481338501, -0.13209271430969238, -0.4787784814834595, -1.3448586463928223, 1.412916660308838, -0.010866083204746246, -0.8007339835166931, 0.639681339263916, -0.9355082511901855, -0.710090160369873, -0.80... |
stochastic gradient free descent | 0.781852 | [-0.4444831609725952, -0.15904076397418976, -0.15669412910938263, -0.8936092257499695, -1.0650999546051025, -0.21864740550518036, 0.11950886249542236, -0.6155262589454651, -1.1887569427490234, 1.6435351371765137, -0.1024329662322998, -0.9245657324790955, 0.45399579405784607, -0.798051118850708, -0.5601736903190613, -0.... |
stochastic gradient descent like | 0.781852 | [-0.6871201992034912, -0.14683908224105835, -0.06964488327503204, -0.8397505879402161, -0.9243080615997314, -0.24963881075382233, 0.18064825236797333, -0.3051362931728363, -1.2639862298965454, 1.4139537811279297, 0.09576525539159775, -0.9663336277008057, 0.3240709602832794, -0.8366860747337341, -0.5159305930137634, -0.... |
stochastic gradient descent based | 0.781852 | [-0.6142354607582092, -0.7185277938842773, -0.1398646980524063, -0.8971508145332336, -0.8309764862060547, -0.20514224469661713, -0.1689751297235489, -0.3693365752696991, -1.2318938970565796, 1.4857650995254517, -0.0691588819026947, -1.0979138612747192, 0.25339433550834656, -1.0188122987747192, -0.34431901574134827, -0.... |
machine learning system | 0.780201 | [-0.21515409648418427, 0.060334183275699615, -0.17862877249717712, -0.24088725447654724, 0.1605527102947235, -1.0952918529510498, 0.8885283470153809, 0.09298327565193176, -0.17441387474536896, 1.1445295810699463, -0.3273234963417053, -1.0840957164764404, -0.02894086204469204, -1.2329738140106201, -0.0893145427107811, -... |
image classification task | 0.770892 | [0.976318359375, -0.324852854013443, -0.2941577732563019, -0.7339459657669067, -0.311993271112442, -0.41833439469337463, 0.4841669201850891, -0.20258617401123047, -0.8928323984146118, 0.7465710639953613, -0.8081284761428833, -0.7779836058616638, 0.46902695298194885, -0.7852662205696106, -0.9808810949325562, -1.13392567... |
medical segmentation | 0.770799 | [0.6822275519371033, 0.6334353685379028, -0.23784607648849487, -0.7374981641769409, -0.9289930462837219, -0.5432345867156982, -0.22437943518161774, 0.4048551321029663, -0.8706067800521851, 0.8119613528251648, -0.7177828550338745, -1.1484870910644531, 0.6838526129722595, -0.6844966411590576, -0.5696386694908142, -0.9903... |
medical image segmentation | 0.770799 | [0.7502228021621704, 0.5538145899772644, -0.31861624121665955, -0.6785168647766113, -0.6610113382339478, -0.6725207567214966, -0.25655731558799744, 0.42365336418151855, -1.0029646158218384, 0.6951742768287659, -0.9784970283508301, -1.2878769636154175, 0.5821637511253357, -0.713211178779602, -0.4553793966770172, -0.9105... |
unsupervised domain adaptation task | 0.769468 | [0.3389263153076172, 0.3718552887439728, -0.08711697906255722, -0.8568892478942871, -0.9050883650779724, -0.8190094828605652, 0.45620235800743103, -0.34992292523384094, -0.9178383946418762, 1.6047600507736206, -0.029238050803542137, -0.18963809311389923, 0.4778486490249634, -0.6854293346405029, -0.7003697752952576, -0.... |
unsupervised domain adaptationuda | 0.769468 | [0.19402937591075897, 0.2452659010887146, -0.25443553924560547, -0.8005450367927551, -1.0105644464492798, -0.9060649871826172, 0.5329912304878235, -0.5567548871040344, -0.7794956564903259, 1.5401378870010376, -0.11863284558057785, -0.303840696811676, 0.3548393249511719, -0.6175333857536316, -0.7019584774971008, -0.5382... |
unsupervised domain adaptation | 0.769468 | [0.30294308066368103, 0.2630532383918762, -0.2520790100097656, -1.0017541646957397, -1.0202184915542603, -0.889620304107666, 0.4478157162666321, -0.35455164313316345, -0.7701647877693176, 1.669500708580017, -0.09402142465114594, -0.38683193922042847, 0.30416420102119446, -0.7886359691619873, -0.6886337995529175, -0.434... |
machine learning task | 0.76915 | [0.3907332420349121, 0.30491015315055847, -0.3064071834087372, -0.5335911512374878, -0.6735376119613647, -0.741065263748169, 0.8317949175834656, 0.20925192534923553, -0.5650016069412231, 1.2317736148834229, 0.08406753838062286, -0.5486516952514648, -0.042668648064136505, -0.672886848449707, -0.3657246232032776, -0.8638... |
knowledge graph application | 0.766938 | [0.024100756272673607, 1.094818115234375, -0.6540361046791077, 0.032936301082372665, 0.5516418218612671, -0.4085482954978943, 0.24960236251354218, 0.574377179145813, 0.12360646575689316, 1.507865309715271, -0.34303006529808044, -1.035273790359497, -0.8644058108329773, -1.9303251504898071, -0.7486230134963989, -0.053242... |
knowledge graph framework | 0.766938 | [-0.4603303372859955, 0.9710292816162109, -0.6492894887924194, -0.021055815741419792, 0.5110907554626465, -0.6216135025024414, 0.5039056539535522, 0.3100338578224182, 0.05393719673156738, 1.33638334274292, -0.000405365222832188, -0.6753652095794678, -0.8616857528686523, -2.070341110229492, -0.7142734527587891, 0.102406... |
knowledge graph domain | 0.766938 | [-0.1744481772184372, 1.237886667251587, -0.7865363359451294, -0.1533307135105133, 0.5890799164772034, -0.5851072669029236, 0.3936828672885895, 0.6740792989730835, 0.11835508048534393, 1.6856157779693604, -0.3199928402900696, -0.9671319723129272, -0.8212749361991882, -2.0924813747406006, -0.7811744213104248, 0.10423097... |
knowledge graph path | 0.766938 | [-0.38567909598350525, 1.1377958059310913, -0.862820029258728, 0.044627729803323746, 0.7637923955917358, -0.6970529556274414, 0.2226930558681488, 0.22958233952522278, 0.11943532526493073, 1.547149896621704, -0.3706914186477661, -1.114974021911621, -0.923191249370575, -1.984954595565796, -0.8181127309799194, 0.257890999... |
knowledge graph model | 0.766938 | [-0.7120547294616699, 0.9399506449699402, -0.8029574155807495, -0.043052367866039276, 0.8649023771286011, -0.39958563446998596, 0.4594312310218811, 0.4473777711391449, -0.009874247014522552, 1.4069629907608032, -0.10725007951259613, -0.8236925005912781, -0.8812547922134399, -2.081225633621216, -0.6668626666069031, 0.35... |
knowledge graph complex | 0.766938 | [-0.28301435708999634, 1.0914829969406128, -0.2978571951389313, 0.08425907045602798, 0.7402053475379944, -0.8858178853988647, 0.45181912183761597, 0.5005730390548706, -0.1344807893037796, 1.5485254526138306, -0.24431368708610535, -0.8165792226791382, -0.8887457847595215, -1.767870306968689, -0.6606510877609253, 0.07751... |
knowledge graph | 0.766938 | [-0.5967503190040588, 1.098996639251709, -0.8810158967971802, 0.013634949922561646, 0.6719238758087158, -0.6295862197875977, 0.23543192446231842, 0.5752686262130737, 0.026248745620250702, 1.6052498817443848, -0.2384902685880661, -0.911280632019043, -0.8512929677963257, -1.929175853729248, -0.7835896611213684, -0.030814... |
knowledge graph describing | 0.766938 | [-0.5743350386619568, 0.9412887692451477, -0.8617299795150757, -0.12096880376338959, 0.7663224935531616, -0.43367868661880493, 0.16699334979057312, 0.5509876012802124, 0.19948890805244446, 1.3040838241577148, 0.1803019493818283, -0.7884395718574524, -0.7719594836235046, -1.7856743335723877, -0.6984561681747437, -0.0438... |
lower bound | 0.76678 | [0.025212405249476433, 0.21365872025489807, -0.7614749670028687, -0.2378784418106079, -0.7354955077171326, -0.8922151327133179, -0.044524382799863815, -0.5792821049690247, -0.3977270722389221, 1.3723669052124023, -0.4720069468021393, -0.8349035978317261, -0.2561541497707367, -1.0224974155426025, -0.43793579936027527, -... |
conditional random field | 0.766121 | [0.10866799205541611, 0.361839234828949, -0.3177548944950104, -0.9596176147460938, -1.2526168823242188, 0.2887689173221588, 0.920577347278595, 0.0986451730132103, -0.2989613115787506, 1.6366279125213623, 0.18526968359947205, -0.524092435836792, 0.25321754813194275, -1.4513604640960693, -0.9337903261184692, -0.855383396... |
artificial reinforcement learning agent | 0.763123 | [-0.36538347601890564, 0.5079682469367981, -0.2926885187625885, 0.5359588265419006, 0.12533658742904663, -0.4470764696598053, 0.7220897078514099, -0.24687522649765015, -0.7793124318122864, 1.7289724349975586, -0.6281177401542664, -0.6327465176582336, 0.11556906253099442, -1.2276042699813843, -0.501679003238678, -0.9115... |
q learning reinforcement agent | 0.763123 | [-0.5913600921630859, 0.35918426513671875, -0.27761760354042053, 0.3124330937862396, -0.5543063282966614, -0.21935546398162842, 0.24910129606723785, -0.22413526475429535, -0.6401345729827881, 1.7371045351028442, -0.35163912177085876, -0.3996089994907379, -0.4794635772705078, -1.166491150856018, -0.4498595893383026, -0.... |
reinforcement learning agent | 0.763123 | [-0.5496652126312256, 0.45176583528518677, -0.3160187304019928, 0.3185485005378723, -0.04030206426978111, -0.41556674242019653, 0.6985659599304199, -0.2329467087984085, -0.6958128809928894, 1.8089344501495361, -0.4490468502044678, -0.5610118508338928, -0.29368290305137634, -1.1788386106491089, -0.5611381530761719, -0.8... |
q learning agent | 0.763123 | [-0.7263065576553345, 0.29555922746658325, -0.3733522891998291, 0.13072869181632996, -0.4768203794956207, -0.2657763659954071, 0.1942526400089264, -0.07750292122364044, -0.6170303225517273, 1.7880370616912842, -0.31063738465309143, -0.45320209860801697, -0.4403332769870758, -1.201489806175232, -0.370478093624115, -0.87... |
graph learning convolutional network | 0.758025 | [-0.12418998032808304, 0.9203310012817383, -0.261766642332077, 0.08046921342611313, 0.4252203404903412, -0.13802926242351532, 0.7011878490447998, 0.6059979796409607, 0.253160685300827, 0.20182311534881592, 0.029039936140179634, -1.09810471534729, 0.01095880102366209, -1.6106466054916382, -0.8942252993583679, -0.3563373... |
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