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Google at ICML 2017

Sunday, August 6, 2017

Posted by Christian Howard, Editor-in-Chief, Research Communications
International Conference on Machine LearningInternational Machine Learning SocietyFacetsNsynthGoogle Brain Residency programblueICML 2017 CommitteesAlex Kulesza, Amr Ahmed, Andrew Dai, Corinna Cortes, George Dahl, Hugo Larochelle, Matthew Hoffman, Maya Gupta, Moritz Hardt, Quoc LeRyan AdamsPublicationsRobust Adversarial Reinforcement LearningLerrel Pinto, James Davidson, Rahul Sukthankar, Abhinav GuptaTight Bounds for Approximate Carathéodory and BeyondVahab Mirrokni, Renato Leme, Adrian Vladu, Sam WongSharp Minima Can Generalize For Deep NetsLaurent Dinh, Razvan Pascanu, Samy Bengio, Yoshua BengioGeometry of Neural Network Loss Surfaces via Random Matrix TheoryJeffrey Pennington, Yasaman BahriConditional Image Synthesis with Auxiliary Classifier GANsAugustus Odena, Christopher Olah, Jon ShlensLearning Deep Latent Gaussian Models with Markov Chain Monte CarloMatthew D. HoffmanOn the Expressive Power of Deep Neural NetworksMaithra Raghu, Ben Poole, Surya Ganguli, Jon Kleinberg, Jascha Sohl-DicksteinAdaNet: Adaptive Structural Learning of Artificial Neural NetworksCorinna Cortes, Xavi Gonzalvo, Vitaly Kuznetsov, Mehryar Mohri, Scott YangLearned Optimizers that Scale and GeneralizeOlga Wichrowska, Niru Maheswaranathan, Matthew Hoffman, Sergio Gomez, Misha Denil, Nando de Freitas, Jascha Sohl-DicksteinAdaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIPSatyen Kale, Zohar Karnin, Tengyuan Liang, David PalAlgorithms for ℓ_p Low-Rank ApproximationFlavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar, Silvio Lattanzi, Rina Panigrahy, David WoodruffConsistent k-ClusteringSilvio Lattanzi, Sergei VassilvitskiiInput Switched Affine Networks: An RNN Architecture Designed for InterpretabilityJakob Foerster, Justin Gilmer, Jan Chorowski, Jascha Sohl-Dickstein, David SussilloOnline and Linear-Time Attention by Enforcing Monotonic AlignmentsColin Raffel, Thang Luong, Peter Liu, Ron Weiss, Douglas EckGradient Boosted Decision Trees for High Dimensional Sparse OutputSi Si, Huan Zhang, Sathiya Keerthi, Dhruv Mahajan, Inderjit Dhillon, Cho-Jui HsiehSequence Tutor: Conservative fine-tuning of sequence generation models with KL-controlNatasha Jaques, Shixiang Gu, Dzmitry Bahdanau, Jose Hernandez-Lobato, Richard E Turner, Douglas EckUniform Convergence Rates for Kernel Density EstimationHeinrich JiangDensity Level Set Estimation on Manifolds with DBSCANHeinrich JiangMaximum Selection and Ranking under Noisy ComparisonsMoein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda SureshNeural Audio Synthesis of Musical Notes with WaveNet AutoencodersCinjon Resnick, Adam Roberts, Jesse Engel, Douglas Eck, Sander Dieleman, Karen Simonyan, Mohammad NorouziDistributed Mean Estimation with Limited CommunicationAnanda Suresh, Felix Yu, Sanjiv Kumar, Brendan McMahanLearning to Generate Long-term Future via Hierarchical PredictionRuben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak LeeVariational Boosting: Iteratively Refining Posterior ApproximationsAndrew Miller, Nicholas J Foti, Ryan AdamsRobustFill: Neural Program Learning under Noisy I/OJacob Devlin, Jonathan Uesato, Surya Bhupatiraju, Rishabh Singh, Abdel-rahman Mohamed, Pushmeet KohliA Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete DistributionsJayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda SureshAxiomatic Attribution for Deep NetworksAnkur Taly, Qiqi Yan,,Mukund SundararajanDifferentiable Programs with Neural LibrariesAlex L Gaunt, Marc Brockschmidt, Nate Kushman, Daniel TarlowLatent LSTM Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence DataManzil Zaheer, Amr Ahmed, Alex SmolaDevice Placement Optimization with Reinforcement LearningAzalia Mirhoseini, Hieu Pham, Quoc Le, Benoit Steiner, Mohammad Norouzi, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Samy Bengio, Jeff DeanCanopy — Fast Sampling with Cover TreesManzil Zaheer, Satwik Kottur, Amr Ahmed, Jose Moura, Alex SmolaZero-Shot Task Generalization with Multi-Task Deep Reinforcement LearningJunhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet KohliProbabilistic Submodular Maximization in Sub-Linear TimeSerban Stan, Morteza Zadimoghaddam, Andreas Krause, Amin KarbasiDeep Value Networks Learn to Evaluate and Iteratively Refine Structured OutputsMichael Gygli, Mohammad Norouzi, Anelia AngelovaStochastic Generative HashingBo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le SongAccelerating Eulerian Fluid Simulation With Convolutional NetworksJonathan Tompson, Kristofer D Schlachter, Pablo Sprechmann, Ken PerlinLarge-Scale Evolution of Image ClassifiersEsteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Jie Tan, Quoc Le, Alexey KurakinNeural Message Passing for Quantum ChemistryJustin Gilmer, Samuel Schoenholz, Patrick Riley, Oriol Vinyals, George DahlNeural Optimizer Search with Reinforcement LearningIrwan Bello, Barret Zoph, Vijay Vasudevan, Quoc LeWorkshopsImplicit Generative ModelsIan GoodfellowLearning to Generate Natural LanguageGenerating High-Quality and Informative Conversation Responses with Sequence-to-Sequence ModelsLouis Shao, Stephan Gouws, Denny Britz, Anna Goldie, Brian Strope, Ray KurzweilLifelong Learning: A Reinforcement Learning ApproachBridging the Gap Between Value and Policy Based Reinforcement LearningOfir Nachum, Mohammad Norouzi, Kelvin Xu, Dale SchuurmansPrincipled Approaches to Deep LearningRobert GensJascha Sohl-DicksteinWorkshop on Human Interpretability in Machine Learning (WHI)Been KimICML Workshop on TinyML: ML on a Test-time Budget for IoT, Mobiles, and Other ApplicationsSujith RaviDeep Structured PredictionGal Chechik, Ofer MeshiVitaly Kuznetsov, Kevin MurphyRyan AdamsFiltering Variational ObjectivesChris J Maddison, Dieterich Lawson, George Tucker, Mohammad Norouzi, Nicolas Heess, Arnaud Doucet, Andriy Mnih, Yee Whye TehREBAR: Low-variance, unbiased gradient estimates for discrete latent variable modelsGeorge Tucker, Andriy Mnih, Chris J Maddison, Dieterich Lawson, Jascha Sohl-DicksteinMachine Learning in Speech and Language ProcessingTara SainathRon WeissPicky Learners: Choosing Alternative Ways to Process Data Tomer KorenCorinna Cortes, Mehryar MohriPrivate and Secure Machine LearningIlya MironovReproducibility in Machine Learning ResearchHugo Larochelle, Francois CholletSamy BengioTime Series WorkshopVitaly KuznetsovTutorialInterpretable Machine LearningBeen Kim