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Google at ICML 2018

Monday, July 9, 2018

Posted by Christian Howard, Editor-in-Chief, Google AI CommunicationsInternational Conference on Machine LearningInternational Machine Learning SocietyTensorFlow HubMagenta projectGoogle AI ResidencICML 2018 CommitteesAndrew McCallum, Corinna Cortes, Hugo Larochelle, William CohenRyan AdamsAccepted PublicationsPredict and Constrain: Modeling Cardinality in Deep Structured PredictionNataly Brukhim, Amir GlobersonQuickshift++: Provably Good Initializations for Sample-Based Mean ShiftHeinrich Jiang, Jennifer Jang, Samory KpotufeLearning a Mixture of Two Multinomial LogitsFlavio Chierichetti, Ravi Kumar, Andrew TomkinsStructured Evolution with Compact Architectures for Scalable Policy OptimizationKrzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E Turner, Adrian WellerFixing a Broken ELBOAlexander Alemi, Ben Poole, Ian Fischer, Joshua Dillon, Rif Saurous, Kevin MurphyHierarchical Long-term Video Prediction without SupervisionNevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak LeeSelf-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory EmbeddingsJohn Co-Reyes, Yu Xuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey LevineWell Tempered LassoYuanzhi Li, Yoram SingerProgrammatically Interpretable Reinforcement LearningAbhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat ChaudhuriDynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural NetworksLechao Xiao, Yasaman Bahri, Jascha Sohl-Dickstein, Samuel Schoenholz, Jeffrey PenningtonOn the Optimization of Deep Networks: Implicit Acceleration by OverparameterizationSanjeev Arora, Nadav Cohen, Elad HazanScalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness ConstraintsEhsan Kazemi, Morteza Zadimoghaddam, Amin KarbasiData Summarization at Scale: A Two-Stage Submodular ApproachMarko Mitrovic, Ehsan Kazemi, Morteza Zadimoghaddam, Amin KarbasiMachine Theory of MindNeil Rabinowitz, Frank Perbet, Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew BotvinickLearning to Optimize Combinatorial FunctionsNir Rosenfeld, Eric Balkanski, Amir Globerson, Yaron SingerProportional Allocation: Simple, Distributed, and Diverse Matching with High EntropyShipra Agarwal, Morteza Zadimoghaddam, Vahab MirrokniPath Consistency Learning in Tsallis Entropy Regularized MDPsYinlam Chow, Ofir Nachum, Mohammad GhavamzadehEfficient Neural Architecture Search via Parameters SharingHieu Pham, Melody Guan, Barret Zoph, Quoc Le, Jeff DeanAdafactor: Adaptive Learning Rates with Sublinear Memory CostNoam Shazeer, Mitchell SternLearning Memory Access PatternsMilad Hashemi, Kevin Swersky, Jamie Smith, Grant Ayers, Heiner Litz, Jichuan Chang, Christos Kozyrakis, Parthasarathy RanganathanSBEED: Convergent Reinforcement Learning with Nonlinear Function ApproximationBo Dai, Albert Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le SongScalable Bilinear Pi Learning Using State and Action FeaturesYichen Chen, Lihong Li, Mengdi WangDistributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter Glynn, Yinyu Ye, Li-Jia Li, Li Fei-FeiShampoo: Preconditioned Stochastic Tensor OptimizationVineet Gupta, Tomer Koren, Yoram SingerParallel and Streaming Algorithms for K-Core DecompositionHossein Esfandiari, Silvio Lattanzi, Vahab MirrokniCan Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?Maithra Raghu, Alexander Irpan, Jacob Andreas, Bobby Kleinberg, Quoc Le, Jon KleinbergIs Generator Conditioning Causally Related to GAN Performance?Augustus Odena, Jacob Buckman, Catherine Olsson, Tom Brown, Christopher Olah, Colin Raffel, Ian GoodfellowThe Mirage of Action-Dependent Baselines in Reinforcement LearningGeorge Tucker, Surya Bhupatiraju, Shixiang Gu, Richard E Turner, Zoubin Ghahramani, Sergey LevineMentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted LabelsLu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, Li Fei-FeiLoss Decomposition for Fast Learning in Large Output SpacesEn-Hsu Yen, Satyen Kale, Felix Xinnan Yu, Daniel Holtmann-Rice, Sanjiv Kumar, Pradeep RavikumarA Hierarchical Latent Vector Model for Learning Long-Term Structure in MusicAdam Roberts, Jesse Engel, Colin Raffel, Curtis Hawthorne, Douglas EckSmoothed Action Value Functions for Learning Gaussian PoliciesOfir Nachum, Mohammad Norouzi, George Tucker, Dale SchuurmansFast Decoding in Sequence Models Using Discrete Latent VariablesLukasz Kaiser, Samy Bengio, Aurko Roy, Ashish Vaswani, Niki Parmar, Jakob Uszkoreit, Noam ShazeerAccelerating Greedy Coordinate Descent MethodsHaihao Lu, Robert Freund, Vahab MirrokniApproximate Leave-One-Out for Fast Parameter Tuning in High DimensionsShuaiwen Wang, Wenda Zhou, Haihao Lu, Arian Maleki, Vahab MirrokniImage TransformerNiki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, Dustin TranTowards End-to-End Prosody Transfer for Expressive Speech Synthesis with TacotronRJ Skerry-Ryan, Eric Battenberg, Ying Xiao, Yuxuan Wang, Daisy Stanton, Joel Shor, Ron Weiss, Robert Clark, Rif SaurousDynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural NetworksMinmin Chen, Jeffrey Pennington,, Samuel SchoenholzStyle Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech SynthesisYuxuan Wang, Daisy Stanton, Yu Zhang, RJ Skerry-Ryan, Eric Battenberg, Joel Shor, Ying Xiao, Ye Jia, Fei Ren, Rif SaurousConstrained Interacting Submodular GroupingsAndrew Cotter, Mahdi Milani Fard, Seungil You, Maya Gupta, Jeff BilmesReinforcing Adversarial Robustness using Model Confidence Induced by Adversarial TrainingXi Wu, Uyeong Jang, Jiefeng Chen, Lingjiao Chen, Somesh JhaInterpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai, James Wexler, Fernanda Viégas, Rory SayresOnline Learning with AbstentionCorinna Cortes, Giulia DeSalvo, Claudio Gentile, Mehryar Mohri, Scott YangOnline Linear Quadratic ControlAlon Cohen, Avinatan Hasidim, Tomer Koren, Nevena Lazic, Yishay Mansour, Kunal TalwarCompetitive Caching with Machine Learned AdviceThodoris Lykouris, Sergei VassilvitskiiEfficient Neural Audio SynthesisNal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aäron van den Oord, Sander Dieleman, Koray KavukcuogluGradient Descent with Identity Initialization Efficiently Learns Positive Definite Linear Transformations by Deep Residual NetworksPeter Bartlett, Dave Helmbold, Phil LongUnderstanding and Simplifying One-Shot Architecture SearchGabriel Bender, Pieter-Jan Kindermans, Barret Zoph, Vijay Vasudevan, Quoc LeApproximation Algorithms for Cascading Prediction ModelsMatthew StreeterLearning Longer-term Dependencies in RNNs with Auxiliary LossesTrieu Trinh, Andrew Dai, Thang Luong, Quoc LeSelf-Imitation LearningJunhyuk Oh, Yijie Guo, Satinder Singh, Honglak LeeAdaptive Sampled Softmax with Kernel Based SamplingGuy Blanc, Steffen RendleWorkshops2018 Workshop on Human Interpretability in Machine Learning (WHI)Been Kim, Kush Varshney, Adrian WellerFernanda Viégas, Martin WattenbergExploration in Reinforcement LearningBen Eysenbach, Surya Bhupatiraju, Shane Gu, Junhyuk Oh, Vincent Vanhoucke, Oriol Vinyals, Doina PrecupTheoretical Foundations and Applications of Deep Generative ModelsHonglak Lee