Google AI Blog: NIPS 2015 and Machine Learning Research at Google

NIPS 2015 and Machine Learning Research at Google

Sunday, December 6, 2015

Posted by Sanjiv Kumar, Research Scientist29^th Annual Conference on Neural Information Processing Systemsmachine learningdeep learningbluePROGRAM ORGANIZERSGeneral ChairsCorinna Cortes, Neil D. LawrenceProgram Committee includes:Samy Bengio, Gal Chechik, Ian Goodfellow, Shakir Mohamed, Ilya SutskeverORAL SESSIONSLearning Theory and Algorithms for Forecasting Non-stationary Time SeriesVitaly Kuznetsov, Mehryar MohriSPOTLIGHT SESSIONSDistributed Submodular Cover: Succinctly Summarizing Massive DataBaharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas KrauseSpatial Transformer NetworksMax Jaderberg, Karen Simonyan, Andrew Zisserman, Koray KavukcuogluPointer NetworksOriol Vinyals, Meire Fortunato, Navdeep JaitlyStructured Transforms for Small-Footprint Deep LearningVikas Sindhwani, Tara Sainath, Sanjiv KumarSpherical Random Features for Polynomial KernelsJeffrey Pennington, Felix Yu, Sanjiv KumarPOSTERSLearning to Transduce with Unbounded MemoryEdward Grefenstette, Karl Moritz Hermann, Mustafa Suleyman, Phil BlunsomDeep Knowledge TracingChris Piech, Jonathan Bassen, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas Guibas, Jascha Sohl-DicksteinHidden Technical Debt in Machine Learning SystemsD Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-Francois Crespo, Dan DennisonGrammar as a Foreign LanguageOriol Vinyals, Lukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever, Geoffrey HintonStochastic Variational Information MaximisationShakir Mohamed, Danilo RezendeEmbedding Inference for Structured Multilabel PredictionFarzaneh Mirzazadeh, Siamak Ravanbakhsh, Bing Xu, Nan Ding, Dale SchuurmansOn the Convergence of Stochastic Gradient MCMC Algorithms with High-Order IntegratorsChangyou Chen, Nan Ding, Lawrence CarinSpectral Norm Regularization of Orthonormal Representations for Graph TransductionRakesh Shivanna, Bibaswan Chatterjee, Raman Sankaran, Chiranjib Bhattacharyya, Francis Bach Differentially Private Learning of Structured Discrete DistributionsIlias Diakonikolas, Moritz Hardt, Ludwig SchmidtNearly Optimal Private LASSOKunal Talwar, Li Zhang, Abhradeep ThakurtaLearning Continuous Control Policies by Stochastic Value GradientsNicolas Heess, Greg Wayne, David Silver, Timothy Lillicrap, Tom Erez, Yuval TassaGradient Estimation Using Stochastic Computation GraphsJohn Schulman, Nicolas Heess, Theophane Weber, Pieter AbbeelScheduled Sampling for Sequence Prediction with Recurrent Neural NetworksSamy Bengio, Oriol Vinyals, Navdeep Jaitly, Noam ShazeerTeaching Machines to Read and ComprehendKarl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil BlunsomBayesian dark knowledgeAnoop Korattikara, Vivek Rathod, Kevin Murphy, Max WellingGeneralization in Adaptive Data Analysis and Holdout ReuseCynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron RothSemi-supervised Sequence LearningAndrew Dai, Quoc LeNatural Neural NetworksGuillaume Desjardins, Karen Simonyan, Razvan Pascanu, Koray KavukcuogluRevenue Optimization against Strategic BuyersAndres Munoz Medina, Mehryar MohriWORKSHOPSFeature Extraction: Modern Questions and ChallengesDmitry Storcheus, Afshin Rostamizadeh, Sanjiv KumarJeffery Pennington, Vikas SindhwaniNIPS Time Series WorkshopMehryar MohriCorinna CortesNonparametric Methods for Large Scale Representation LearningAmr AhmedMachine Learning for Spoken Language Understanding and InteractionLarry HeckAdaptive Data AnalysisMoritz HardtDeep Reinforcement LearningDavid SilverSergey LevineAdvances in Approximate Bayesian InferenceShakir MohamedDanilo RezendeCognitive Computation: Integrating Neural and Symbolic Approaches Ramanathan V. Guha, Geoffrey Hinton, Greg WayneTransfer and Multi-Task Learning: Trends and New Perspectives Mehryar MohriAndres Munoz MedinaLearning and privacy with incomplete data and weak supervisionFelix YuAlexander Blocker, Krzysztof Choromanski, Sanjiv KumarNando de FreitasBlack Box Learning and InferenceAli EslamiGeoff HintonQuantum Machine LearningHartmut NevenBayesian Nonparametrics: The Next GenerationAmr AhmedBayesian Optimization: Scalability and FlexibilityNando de FreitasReasoning, Attention, Memory (RAM)Alex Graves, Ilya SutskeverExtreme Classification 2015: Multi-class and Multi-label Learning in Extremely Large Label SpacesMehryar MohriSamy BengioSamy BengioMachine Learning SystemsJeff DeanSYMPOSIABrains, Mind and MachinesGeoffrey Hinton, Demis HassabisDeep Learning SymposiumSamy Bengio, Phil Blunsom, Nando De Freitas, Ilya Sutskever, Andrew ZissermanMax Jaderberg, Sergey Ioffe, Alexander GravesAlgorithms Among Us: The Societal Impacts of Machine LearningShane LeggTUTORIALSNIPS 2015 Deep Learning TutorialGeoffrey E. Hinton, Yoshua Bengio, Yann LeCun
Large-Scale Distributed Systems for Training Neural NetworksJeff Dean, Oriol Vinyals

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NIPS 2015 and Machine Learning Research at Google

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