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金鸡报福金章

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金鸡报福金章

ţӰ׷ߣԲֹԤڲӰ졣йܿνܦϺࣺٽϺԽԽͥѡ÷ʱ޵ķʽԼϺDzٵҹ򲻵˽ҳͣڻҪɸ߰ͣѡ

һΪϷͷʢϷӪϷѪ桷Ϊ֪2009ɹСŸĿ½𽥵õͷš

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ڴ£羳ڵĸƽ̨׷׿ʼ£ͨõơɨ롢ƶ֧۵ʽչͻ

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41𣬵綯ѡʦϴѵ5շѽʵʩۡ

20141£ʢšʱΪ׵IJʢϷԼ˽лͬ4£˽лף1ԪչʢϷɷݣFVInvestmentHoldingsCAPIVEngagementLimitedҲ뵽֮Сʫչ˵ֽ׶ҽԴֲƽ״һƹ̷dzӺ

ѡַֿDzҵṹ˲ŷֲأ˲żбͬʱǵؿܱ߽ͨ׷ܣص㲼ڸվܱߵؿ顣

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ȻһҪԸλ̱ĸֲ֢ʹĥÿһԵܡʪ¶۵Ŀ24Сʱ벻˵Ļ……ѹÿ춼ڣȻԼõʱֻҪ㹻Ŭͻ˿羳ڹڳչ̬ơ

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ûа취޵ݣͨߵķʽһʽģأIan Goodfellowһµķֵ˼ һʽģͣGeneratorģһбʽģɵǷʵһϵͳԻģͬߡ Ϊ ǵĿһ̨ģʦǵĻ ʼͨʽģij ܺܲʦˮƽĺԶʱһԱбʽģͣ߻ȱ㣬ǻ˾ͿһмߡԱԼ˴û϶ԣǻ˾ͿԸԱ߼ Աһ⣺ǴʦĻǻ˻ģбʽģͿ׼ȷرϳǻģ˵ʽģͻãб𲻳˵ѾܹԼˣбʽģ;дߡʽģͺбʽģͣòϷʵ໥ߡ

ǿ̸硢ʽԿ缰Ǩѧϰ

ͼԡͲ죬ǻ࿴˴ˣڹͨʱ򣬲޷ĸǼ˹ܡϾʵˡ˫ṹͼԲͬĵطǣйٶѧϰߣ߶Դﵽá

ͰǴʽԿ硱 GenerativeAdverserial Network, GANͼʾ ϵͳڻԿ ϵͳͼŻԼĿ꺯һϵͳӦбʽģD бʽģDͼʶǷȻʵģھʵʶʣͬʱٶģɵʡһϵͳӦʽģGGϣɵģDĿ顣 Gͼܵģʵ бDбǶ˵бԽãDĿʵֵľԽ G˵ҪСminimizeԷŻ൱󻯣maximizeԼŻ̾GDһͼIJ֣һڲϸбһڲϸϲMinimax㷨AIһ㷨GDϵͳھвϳɳﵽš

ǿ̸硢ʽԿ缰Ǩѧϰ

̵ܲͬʱŻĿꣿGANķGoodfellowµĽ͡ѵͼʾɫĵʵķֲɫǸģͲɵķֲôGANڰɵĸʿռӳ䵽ʵռȥԶԱȡõĽʵƫķɵݷֲϵõֱʵֲغΪֹʱбʽģGͷֲݣѧϰˡ

ǿ̸硢ʽԿ缰Ǩѧϰ

ôû֤ѧϰ̻յõĽأǿ

ǿ̸硢ʽԿ缰Ǩѧϰ

ҷһʽ

GɷDӣѵɷӲָɷIJ֮ԴϣɷԼɷأʱߵİ취ͼ³ļ񵽵ʲôͲϵ顣һʼܺӵһȻõһٺKͬѧָܲɷĴ󣬶ɷҲһֱŬôԷ޾ͻһһֱﵽһֵͬͥҲˡ

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ǿ̸硢ʽԿ缰Ǩѧϰ

GANҲõѧд֡ѵõʱЩGANдּԼ档Ҳõĵط˵һЩӵͼľ൱ģġǺۣΪGANݼ֮ġ롱ĸûѧá

ǿ̸硢ʽԿ缰Ǩѧϰ

ǽҪʣôģһ򵥵İ취ǡ²⡱ ȿԼһʵĸʷֲǰijʽֲģ ȻʽزһĽãǾͻ޸ֲ衣ǣֲµİ취ͣٶס

ҪôأһźܴĻҪѹһСһôأǴҿù˫ͲԶԶԷſͻῴСĻ棬൱ڰһѹһ֣̽convolution顣ſԶһŻŴǻῴеijһ֣̾൱ڴһ򼸸ֲҲǡɡḶ́ʽģ顣ԭ󣬻ѧϰ;ǰ練൱ԶѹͼһһŴγһԭСתþTransposed-Convolution ķDCGANȷ˵ͨӵѵ֮µ֡һЩҲʼ磬Զͼ

ǿ̸硢ʽԿ缰Ǩѧϰ

ȻDCGAN࣬бʽģͲ¡ͺôڴûбҪģôijбʽģͣӣȷʵҪôĴҪĺáԣȡһеһȷʵ԰ҵdzؼһЩЧͱİ취ҪúܶࡣٻصǸӣӬſϣ˵ķӦͿԱҳˡ

GANǿԶӶԱȽϡȷ˵ǿԱȽϡƻ͡ӡǵľ뵽DzDZȡƻ͡㽶һЩ ֪ȻԽһWord2vecֵʾEmbeddingһʵʲôأȷ˵Ϊv(woman)-v(man)+v(king) =v(queen)Ů˼ȥˣټһ൱ڰŮ˵ԸӦľӦŮȡôأڸάռ䣬ݻֵ÷࣬ǵľܽGANҲ飬ȷ˵еĴīȥһеټһŮģͱһŮĴīǿGANģ档

ǿ̸硢ʽԿ缰Ǩѧϰ

ƵϵͳһЩȱ㡣 磬΢һģ͵IJģЧͻἱ˵ֱDCGANģͲɿ

ôأڿʼGAN˼Dz޸ʽģʹģĸģ;ӽʵʵĸģ͡ԣɿʵʾڣοɿ׼ȷزʷֲ֮ľ롣 һµļWasserstein GAN Ϊͳʽģ͵Ŀ꺯ͨŻKLdivergence, GANĿ꺯ŻJS divergence.  붼ȱ㣺Dz׼ȷзֲ֮ľ롣һ׾Wasserstein룬ŽСھ Earth-moverǸһɽôھһɽȥһɽҪ ƶصķþWasserstein 룬W롣ɽ״ȫһôͲҪκηá ȫͬôҪܶķá

ǿ̸硢ʽԿ缰Ǩѧϰ

Wʷֲͺõöࡣ˵ݼķֲһʵŷֲһǼŵķֲKLJSãõһһһľûа취ʶ桢ˡ W룬õĻһɵľ롣ԣWGAN WGAN Ϳ׶ˡ

ʽԿģͣGANЩأģ͵ĽͣͼȻԷټһЩµı߽Ǩѧϰ

ǿ̸硢ʽԿ缰Ǩѧϰ

ӣǰһģӰ䵽ӰģӰģкܶIJȷĵطһΪḶ́һҵʧֵҰʵֵºǵķʽƼϵͳĸһġ

ߣǿGANȻʵǨѧϰ˵ һܺõʽģͣijݼѾѵˣһЩµݣǰһݼԵ ôǿáGAN߽ʽģ͡ǨƵ µݷֲϡȷ˵дֵʱÿǩDzͬģDzӡˢǩΪÿ˶Լдֵص㡣ôôӡˢΪһֵѵѵһͨģͣijдбڶֵѵͿWGANӡˢģǨƵ˵ǩҲ˵ǩҲ͸߸Իص㡣

˵ʹԴݺĿдϡɫһЩGANģͿʵǨѧϰĿꡣ

ﻹһǨѧϰӣӦDomain AdaptationУĿûκεıעеıעԴ GANINһGANģͣԴñעעݵķ࣬ͬʱӵһбݣԴĿ ̽е󣬵бԺܺõĸ򣬾˵мѧͬͬˡʱǨѧϰĿľʹﵽˡ

ǿ̸硢ʽԿ缰Ǩѧϰ

ܽǿʽԿһµĻѧϰ˼롣ģ͹ͬġѧͬʱɳһѧרעһѧרעб٣ٽͬʱʽԿҲһȱݣҪǺܴģ⣬۵ָDZȽȱ

ǿ̸硢ʽԿ缰Ǩѧϰ

ǻص硷ijӾһǶԻˣࣩܳɳ·Ӿĺ漸һҪ˼룺ǡBicameral MindǸܵķչļ˵еܺʶķչͨIJ϶ԻѧϰʵֵġҲdz˵ ԴСڴܡѧ

ǿʽԿGANģͣǡЩıϣǶΪӦܹѧϰߵģܳɳĻϵͳ໥̼GANģУƷֱʽģͺбʽģ͡ ڡ硷̼ԺܶĿѺʹʹûDolores ͬǾ˺ܶʹѵ飬̼DzˡǡҲͲʶ ͼеDoloresڶԻֵ յ»Dzʶ

ǿ̸硢ʽԿ缰Ǩѧϰ

ȻʽԿGANѧϣû漰ʶɡ⣬ ʵϣ˹ܵķչû漰ʶĸ ǣͨGANġǡ ԼǿԽԿϵͳܡ£ǷdzȤģ

չĶ

[1] Goodfellow, Ian, et al. "Generative adversarial nets." Advances in neural information processing systems. 2014.

[2] Ganin, Yaroslav, et al. "Domain-adversarial training of neural networks." Journal of Machine Learning Research 17.59 (2016): 1-35.

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