| 2016 | A Box-Constrained Approach for Hard Permutation Problems. Cong Han Lim, Steve Wright |
| 2016 | A Comparative Analysis and Study of Multiview CNN Models for Joint Object Categorization and Pose Estimation. Mohamed Elhoseiny, Tarek El-Gaaly, Amr Bakry, Ahmed M. Elgammal |
| 2016 | A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery. Ian En-Hsu Yen, Xin Lin, Jiong Zhang, Pradeep Ravikumar, Inderjit S. Dhillon |
| 2016 | A Convolutional Attention Network for Extreme Summarization of Source Code. Miltiadis Allamanis, Hao Peng, Charles Sutton |
| 2016 | A Deep Learning Approach to Unsupervised Ensemble Learning. Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph T. Chang, Yuval Kluger |
| 2016 | A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models. Trong Nghia Hoang, Quang Minh Hoang, Bryan Kian Hsiang Low |
| 2016 | A Kernel Test of Goodness of Fit. Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton |
| 2016 | A Kernelized Stein Discrepancy for Goodness-of-fit Tests. Qiang Liu, Jason D. Lee, Michael I. Jordan |
| 2016 | A Kronecker-factored approximate Fisher matrix for convolution layers. Roger B. Grosse, James Martens |
| 2016 | A Neural Autoregressive Approach to Collaborative Filtering. Yin Zheng, Bangsheng Tang, Wenkui Ding, Hanning Zhou |
| 2016 | A New PAC-Bayesian Perspective on Domain Adaptation. Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant |
| 2016 | A Random Matrix Approach to Echo-State Neural Networks. Romain Couillet, Gilles Wainrib, Hafiz Tiomoko Ali, Harry Sevi |
| 2016 | A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization. Frank E. Curtis |
| 2016 | A Simple and Provable Algorithm for Sparse Diagonal CCA. Megasthenis Asteris, Anastasios Kyrillidis, Oluwasanmi Koyejo, Russell A. Poldrack |
| 2016 | A Simple and Strongly-Local Flow-Based Method for Cut Improvement. Nate Veldt, David F. Gleich, Michael W. Mahoney |
| 2016 | A Subspace Learning Approach for High Dimensional Matrix Decomposition with Efficient Column/Row Sampling. Mostafa Rahmani, George K. Atia |
| 2016 | A Superlinearly-Convergent Proximal Newton-type Method for the Optimization of Finite Sums. Anton Rodomanov, Dmitry Kropotov |
| 2016 | A Theory of Generative ConvNet. Jianwen Xie, Yang Lu, Song-Chun Zhu, Ying Nian Wu |
| 2016 | A Variational Analysis of Stochastic Gradient Algorithms. Stephan Mandt, Matthew D. Hoffman, David M. Blei |
| 2016 | A ranking approach to global optimization. Cédric Malherbe, Emile Contal, Nicolas Vayatis |
| 2016 | ADIOS: Architectures Deep In Output Space. Moustapha Cissé, Maruan Al-Shedivat, Samy Bengio |
| 2016 | Accurate Robust and Efficient Error Estimation for Decision Trees. Lixin Fan |
| 2016 | Actively Learning Hemimetrics with Applications to Eliciting User Preferences. Adish Singla, Sebastian Tschiatschek, Andreas Krause |
| 2016 | Adaptive Algorithms for Online Convex Optimization with Long-term Constraints. Rodolphe Jenatton, Jim C. Huang, Cédric Archambeau |
| 2016 | Adaptive Sampling for SGD by Exploiting Side Information. Siddharth Gopal |
| 2016 | Additive Approximations in High Dimensional Nonparametric Regression via the SALSA. Kirthevasan Kandasamy, Yaoliang Yu |
| 2016 | Algorithms for Optimizing the Ratio of Submodular Functions. Wenruo Bai, Rishabh K. Iyer, Kai Wei, Jeff A. Bilmes |
| 2016 | An optimal algorithm for the Thresholding Bandit Problem. Andrea Locatelli, Maurilio Gutzeit, Alexandra Carpentier |
| 2016 | Analysis of Deep Neural Networks with Extended Data Jacobian Matrix. Shengjie Wang, Abdel-rahman Mohamed, Rich Caruana, Jeff A. Bilmes, Matthai Philipose, Matthew Richardson, Krzysztof J. Geras, Gregor Urban, Özlem Aslan |
| 2016 | Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation. David P. Wipf |
| 2016 | Anytime Exploration for Multi-armed Bandits using Confidence Information. Kwang-Sung Jun, Robert D. Nowak |
| 2016 | Anytime optimal algorithms in stochastic multi-armed bandits. Rémy Degenne, Vianney Perchet |
| 2016 | Ask Me Anything: Dynamic Memory Networks for Natural Language Processing. Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, Richard Socher |
| 2016 | Associative Long Short-Term Memory. Ivo Danihelka, Greg Wayne, Benigno Uria, Nal Kalchbrenner, Alex Graves |
| 2016 | Asymmetric Multi-task Learning based on Task Relatedness and Confidence. Giwoong Lee, Eunho Yang, Sung Ju Hwang |
| 2016 | Asynchronous Methods for Deep Reinforcement Learning. Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu |
| 2016 | Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification. Yuting Zhang, Kibok Lee, Honglak Lee |
| 2016 | Autoencoding beyond pixels using a learned similarity metric. Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, Ole Winther |
| 2016 | Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series. Yunseong Hwang, Anh Tong, Jaesik Choi |
| 2016 | Auxiliary Deep Generative Models. Lars Maaløe, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther |
| 2016 | BASC: Applying Bayesian Optimization to the Search for Global Minima on Potential Energy Surfaces. Shane Carr, Roman Garnett, Cynthia Lo |
| 2016 | BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits. Alexander Rakhlin, Karthik Sridharan |
| 2016 | Barron and Cover's Theory in Supervised Learning and its Application to Lasso. Masanori Kawakita, Jun'ichi Takeuchi |
| 2016 | Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach |
| 2016 | Benchmarking Deep Reinforcement Learning for Continuous Control. Yan Duan, Xi Chen, Rein Houthooft, John Schulman, Pieter Abbeel |
| 2016 | Beyond CCA: Moment Matching for Multi-View Models. Anastasia Podosinnikova, Francis R. Bach, Simon Lacoste-Julien |
| 2016 | Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference. Tudor Achim, Ashish Sabharwal, Stefano Ermon |
| 2016 | Bidirectional Helmholtz Machines. Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio |
| 2016 | Binary embeddings with structured hashed projections. Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski, Tony Jebara, Sanjiv Kumar, Yann LeCun |
| 2016 | Black-Box Alpha Divergence Minimization. José Miguel Hernández-Lobato, Yingzhen Li, Mark Rowland, Thang D. Bui, Daniel Hernández-Lobato, Richard E. Turner |
| 2016 | Black-box Optimization with a Politician. Sébastien Bubeck, Yin Tat Lee |
| 2016 | Boolean Matrix Factorization and Noisy Completion via Message Passing. Siamak Ravanbakhsh, Barnabás Póczos, Russell Greiner |
| 2016 | Bounded Off-Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design. William Hoiles, Mihaela van der Schaar |
| 2016 | Clustering High Dimensional Categorical Data via Topographical Features. Chao Chen, Novi Quadrianto |
| 2016 | Collapsed Variational Inference for Sum-Product Networks. Han Zhao, Tameem Adel, Geoffrey J. Gordon, Brandon Amos |
| 2016 | Community Recovery in Graphs with Locality. Yuxin Chen, Govinda M. Kamath, Changho Suh, David Tse |
| 2016 | Complex Embeddings for Simple Link Prediction. Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, Guillaume Bouchard |
| 2016 | Compressive Spectral Clustering. Nicolas Tremblay, Gilles Puy, Rémi Gribonval, Pierre Vandergheynst |
| 2016 | Computationally Efficient Nyström Approximation using Fast Transforms. Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon |
| 2016 | Conditional Bernoulli Mixtures for Multi-label Classification. Cheng Li, Bingyu Wang, Virgil Pavlu, Javed A. Aslam |
| 2016 | Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications. Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath |
| 2016 | Conservative Bandits. Yifan Wu, Roshan Shariff, Tor Lattimore, Csaba Szepesvári |
| 2016 | Contextual Combinatorial Cascading Bandits. Shuai Li, Baoxiang Wang, Shengyu Zhang, Wei Chen |
| 2016 | Continuous Deep Q-Learning with Model-based Acceleration. Shixiang Gu, Timothy P. Lillicrap, Ilya Sutskever, Sergey Levine |
| 2016 | Control of Memory, Active Perception, and Action in Minecraft. Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee |
| 2016 | Controlling the distance to a Kemeny consensus without computing it. Yunlong Jiao, Anna Korba, Eric Sibony |
| 2016 | Convergence of Stochastic Gradient Descent for PCA. Ohad Shamir |
| 2016 | Convolutional Rectifier Networks as Generalized Tensor Decompositions. Nadav Cohen, Amnon Shashua |
| 2016 | Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm. Junpei Komiyama, Junya Honda, Hiroshi Nakagawa |
| 2016 | Correcting Forecasts with Multifactor Neural Attention. Matthew Riemer, Aditya Vempaty, Flávio P. Calmon, Fenno F. Terry Heath III, Richard Hull, Elham Khabiri |
| 2016 | Correlation Clustering and Biclustering with Locally Bounded Errors. Gregory J. Puleo, Olgica Milenkovic |
| 2016 | Cross-Graph Learning of Multi-Relational Associations. Hanxiao Liu, Yiming Yang |
| 2016 | CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy. Ran Gilad-Bachrach, Nathan Dowlin, Kim Laine, Kristin E. Lauter, Michael Naehrig, John Wernsing |
| 2016 | Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control. Prashanth L. A., Cheng Jie, Michael C. Fu, Steven I. Marcus, Csaba Szepesvári |
| 2016 | DCM Bandits: Learning to Rank with Multiple Clicks. Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Zheng Wen |
| 2016 | DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression. Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh |
| 2016 | Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning. Philip S. Thomas, Emma Brunskill |
| 2016 | Data-driven Rank Breaking for Efficient Rank Aggregation. Ashish Khetan, Sewoong Oh |
| 2016 | Dealbreaker: A Nonlinear Latent Variable Model for Educational Data. Andrew S. Lan, Tom Goldstein, Richard G. Baraniuk, Christoph Studer |
| 2016 | Deconstructing the Ladder Network Architecture. Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron C. Courville, Yoshua Bengio |
| 2016 | Deep Gaussian Processes for Regression using Approximate Expectation Propagation. Thang D. Bui, Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Yingzhen Li, Richard E. Turner |
| 2016 | Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin. Dario Amodei, Sundaram Ananthanarayanan, Rishita Anubhai, Jingliang Bai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse H. Engel, Linxi Fan, Christopher Fougner, Awni Y. Hannun, Billy Jun, Tony Han, Patrick LeGresley, Xiangang Li, Libby Lin, Sharan Narang, Andrew Y. Ng, Sherjil Ozair, Ryan Prenger, Sheng Qian, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Chong Wang, Yi Wang, Zhiqian Wang, Bo Xiao, Yan Xie, Dani Yogatama, Jun Zhan, Zhenyao Zhu |
| 2016 | Deep Structured Energy Based Models for Anomaly Detection. Shuangfei Zhai, Yu Cheng, Weining Lu, Zhongfei Zhang |
| 2016 | Dictionary Learning for Massive Matrix Factorization. Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux |
| 2016 | Differential Geometric Regularization for Supervised Learning of Classifiers. Qinxun Bai, Steven Rosenberg, Zheng Wu, Stan Sclaroff |
| 2016 | Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing. Marco Gaboardi, Hyun-Woo Lim, Ryan M. Rogers, Salil P. Vadhan |
| 2016 | Differentially Private Policy Evaluation. Borja Balle, Maziar Gomrokchi, Doina Precup |
| 2016 | Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data. Sandhya Prabhakaran, Elham Azizi, Ambrose J. Carr, Dana Pe'er |
| 2016 | Discrete Deep Feature Extraction: A Theory and New Architectures. Thomas Wiatowski, Michael Tschannen, Aleksandar Stanic, Philipp Grohs, Helmut Bölcskei |
| 2016 | Discrete Distribution Estimation under Local Privacy. Peter Kairouz, Kallista A. Bonawitz, Daniel Ramage |
| 2016 | Discriminative Embeddings of Latent Variable Models for Structured Data. Hanjun Dai, Bo Dai, Le Song |
| 2016 | Distributed Clustering of Linear Bandits in Peer to Peer Networks. Nathan Korda, Balázs Szörényi, Shuai Li |
| 2016 | Diversity-Promoting Bayesian Learning of Latent Variable Models. Pengtao Xie, Jun Zhu, Eric P. Xing |
| 2016 | Domain Adaptation with Conditional Transferable Components. Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, Bernhard Schölkopf |
| 2016 | Doubly Decomposing Nonparametric Tensor Regression. Masaaki Imaizumi, Kohei Hayashi |
| 2016 | Doubly Robust Off-policy Value Evaluation for Reinforcement Learning. Nan Jiang, Lihong Li |
| 2016 | Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning. Yarin Gal, Zoubin Ghahramani |
| 2016 | Dropout distillation. Samuel Rota Bulò, Lorenzo Porzi, Peter Kontschieder |
| 2016 | Dueling Network Architectures for Deep Reinforcement Learning. Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas |
| 2016 | Dynamic Capacity Networks. Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, Aaron C. Courville |
| 2016 | Dynamic Memory Networks for Visual and Textual Question Answering. Caiming Xiong, Stephen Merity, Richard Socher |
| 2016 | Early and Reliable Event Detection Using Proximity Space Representation. Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy |
| 2016 | Efficient Algorithms for Adversarial Contextual Learning. Vasilis Syrgkanis, Akshay Krishnamurthy, Robert E. Schapire |
| 2016 | Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis. Rong Ge, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford |
| 2016 | Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity. Quanming Yao, James T. Kwok |
| 2016 | Efficient Multi-Instance Learning for Activity Recognition from Time Series Data Using an Auto-Regressive Hidden Markov Model. Xinze Guan, Raviv Raich, Weng-Keen Wong |
| 2016 | Efficient Private Empirical Risk Minimization for High-dimensional Learning. Shiva Prasad Kasiviswanathan, Hongxia Jin |
| 2016 | Energetic Natural Gradient Descent. Philip S. Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill |
| 2016 | Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling. Christopher De Sa, Christopher Ré, Kunle Olukotun |
| 2016 | Epigraph projections for fast general convex programming. Po-Wei Wang, Matt Wytock, J. Zico Kolter |
| 2016 | Estimating Accuracy from Unlabeled Data: A Bayesian Approach. Emmanouil Antonios Platanios, Avinava Dubey, Tom M. Mitchell |
| 2016 | Estimating Cosmological Parameters from the Dark Matter Distribution. Siamak Ravanbakhsh, Junier B. Oliva, Sebastian Fromenteau, Layne Price, Shirley Ho, Jeff G. Schneider, Barnabás Póczos |
| 2016 | Estimating Maximum Expected Value through Gaussian Approximation. Carlo D'Eramo, Marcello Restelli, Alessandro Nuara |
| 2016 | Estimating Structured Vector Autoregressive Models. Igor Melnyk, Arindam Banerjee |
| 2016 | Estimation from Indirect Supervision with Linear Moments. Aditi Raghunathan, Roy Frostig, John C. Duchi, Percy Liang |
| 2016 | Evasion and Hardening of Tree Ensemble Classifiers. Alex Kantchelian, J. D. Tygar, Anthony D. Joseph |
| 2016 | Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling. Zeyuan Allen Zhu, Zheng Qu, Peter Richtárik, Yang Yuan |
| 2016 | Exact Exponent in Optimal Rates for Crowdsourcing. Chao Gao, Yu Lu, Dengyong Zhou |
| 2016 | Experimental Design on a Budget for Sparse Linear Models and Applications. Sathya N. Ravi, Vamsi K. Ithapu, Sterling C. Johnson, Vikas Singh |
| 2016 | Exploiting Cyclic Symmetry in Convolutional Neural Networks. Sander Dieleman, Jeffrey De Fauw, Koray Kavukcuoglu |
| 2016 | Expressiveness of Rectifier Networks. Xingyuan Pan, Vivek Srikumar |
| 2016 | Extended and Unscented Kitchen Sinks. Edwin V. Bonilla, Daniel M. Steinberg, Alistair Reid |
| 2016 | Extreme F-measure Maximization using Sparse Probability Estimates. Kalina Jasinska, Krzysztof Dembczynski, Róbert Busa-Fekete, Karlson Pfannschmidt, Timo Klerx, Eyke Hüllermeier |
| 2016 | Factored Temporal Sigmoid Belief Networks for Sequence Learning. Jiaming Song, Zhe Gan, Lawrence Carin |
| 2016 | False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking. Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Yuan Yao |
| 2016 | Fast Algorithms for Segmented Regression. Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt |
| 2016 | Fast Constrained Submodular Maximization: Personalized Data Summarization. Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi |
| 2016 | Fast DPP Sampling for Nystrom with Application to Kernel Methods. Chengtao Li, Stefanie Jegelka, Suvrit Sra |
| 2016 | Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching. Mu Niu, Simon Rogers, Maurizio Filippone, Dirk Husmeier |
| 2016 | Fast Rate Analysis of Some Stochastic Optimization Algorithms. Chao Qu, Huan Xu, Chong Jin Ong |
| 2016 | Fast Stochastic Algorithms for SVD and PCA: Convergence Properties and Convexity. Ohad Shamir |
| 2016 | Fast k-Nearest Neighbour Search via Dynamic Continuous Indexing. Ke Li, Jitendra Malik |
| 2016 | Fast k-means with accurate bounds. James Newling, François Fleuret |
| 2016 | Fast methods for estimating the Numerical rank of large matrices. Shashanka Ubaru, Yousef Saad |
| 2016 | Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier. Jacob D. Abernethy, Elad Hazan |
| 2016 | Faster Eigenvector Computation via Shift-and-Invert Preconditioning. Dan Garber, Elad Hazan, Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford |
| 2016 | Fixed Point Quantization of Deep Convolutional Networks. Darryl Dexu Lin, Sachin S. Talathi, V. Sreekanth Annapureddy |
| 2016 | ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission. Jinsung Yoon, Ahmed M. Alaa, Scott Hu, Mihaela van der Schaar |
| 2016 | From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification. André F. T. Martins, Ramón Fernandez Astudillo |
| 2016 | Gaussian process nonparametric tensor estimator and its minimax optimality. Heishiro Kanagawa, Taiji Suzuki, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami |
| 2016 | Gaussian quadrature for matrix inverse forms with applications. Chengtao Li, Suvrit Sra, Stefanie Jegelka |
| 2016 | Generalization Properties and Implicit Regularization for Multiple Passes SGM. Junhong Lin, Raffaello Camoriano, Lorenzo Rosasco |
| 2016 | Generalization and Exploration via Randomized Value Functions. Ian Osband, Benjamin Van Roy, Zheng Wen |
| 2016 | Generalized Direct Change Estimation in Ising Model Structure. Farideh Fazayeli, Arindam Banerjee |
| 2016 | Generative Adversarial Text to Image Synthesis. Scott E. Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee |
| 2016 | Geometric Mean Metric Learning. Pourya Zadeh, Reshad Hosseini, Suvrit Sra |
| 2016 | Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon |
| 2016 | Graying the black box: Understanding DQNs. Tom Zahavy, Nir Ben-Zrihem, Shie Mannor |
| 2016 | Greedy Column Subset Selection: New Bounds and Distributed Algorithms. Jason M. Altschuler, Aditya Bhaskara, Gang Fu, Vahab S. Mirrokni, Afshin Rostamizadeh, Morteza Zadimoghaddam |
| 2016 | Gromov-Wasserstein Averaging of Kernel and Distance Matrices. Gabriel Peyré, Marco Cuturi, Justin Solomon |
| 2016 | Group Equivariant Convolutional Networks. Taco Cohen, Max Welling |
| 2016 | Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization. Chelsea Finn, Sergey Levine, Pieter Abbeel |
| 2016 | Hawkes Processes with Stochastic Excitations. Young Lee, Kar Wai Lim, Cheng Soon Ong |
| 2016 | Heteroscedastic Sequences: Beyond Gaussianity. Oren Anava, Shie Mannor |
| 2016 | Hierarchical Compound Poisson Factorization. Mehmet Emin Basbug, Barbara E. Engelhardt |
| 2016 | Hierarchical Decision Making In Electricity Grid Management. Gal Dalal, Elad Gilboa, Shie Mannor |
| 2016 | Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams. Roy J. Adams, Nazir Saleheen, Edison Thomaz, Abhinav Parate, Santosh Kumar, Benjamin M. Marlin |
| 2016 | Hierarchical Variational Models. Rajesh Ranganath, Dustin Tran, David M. Blei |
| 2016 | Horizontally Scalable Submodular Maximization. Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause |
| 2016 | How to Fake Multiply by a Gaussian Matrix. Michael Kapralov, Vamsi K. Potluru, David P. Woodruff |
| 2016 | Hyperparameter optimization with approximate gradient. Fabian Pedregosa |
| 2016 | Importance Sampling Tree for Large-scale Empirical Expectation. Olivier Canévet, Cijo Jose, François Fleuret |
| 2016 | Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives. Zeyuan Allen Zhu, Yang Yuan |
| 2016 | Inference Networks for Sequential Monte Carlo in Graphical Models. Brooks Paige, Frank D. Wood |
| 2016 | Interacting Particle Markov Chain Monte Carlo. Tom Rainforth, Christian A. Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem van de Meent, Arnaud Doucet, Frank D. Wood |
| 2016 | Interactive Bayesian Hierarchical Clustering. Sharad Vikram, Sanjoy Dasgupta |
| 2016 | Isotonic Hawkes Processes. Yichen Wang, Bo Xie, Nan Du, Le Song |
| 2016 | K-Means Clustering with Distributed Dimensions. Hu Ding, Yu Liu, Lingxiao Huang, Jian Li |
| 2016 | L1-regularized Neural Networks are Improperly Learnable in Polynomial Time. Yuchen Zhang, Jason D. Lee, Michael I. Jordan |
| 2016 | Large-Margin Softmax Loss for Convolutional Neural Networks. Weiyang Liu, Yandong Wen, Zhiding Yu, Meng Yang |
| 2016 | Learning Convolutional Neural Networks for Graphs. Mathias Niepert, Mohamed Ahmed, Konstantin Kutzkov |
| 2016 | Learning End-to-end Video Classification with Rank-Pooling. Basura Fernando, Stephen Gould |
| 2016 | Learning Granger Causality for Hawkes Processes. Hongteng Xu, Mehrdad Farajtabar, Hongyuan Zha |
| 2016 | Learning Mixtures of Plackett-Luce Models. Zhibing Zhao, Peter Piech, Lirong Xia |
| 2016 | Learning Physical Intuition of Block Towers by Example. Adam Lerer, Sam Gross, Rob Fergus |
| 2016 | Learning Population-Level Diffusions with Generative RNNs. Tatsunori B. Hashimoto, David K. Gifford, Tommi S. Jaakkola |
| 2016 | Learning Representations for Counterfactual Inference. Fredrik D. Johansson, Uri Shalit, David A. Sontag |
| 2016 | Learning Simple Algorithms from Examples. Wojciech Zaremba, Tomás Mikolov, Armand Joulin, Rob Fergus |
| 2016 | Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization. Eric Balkanski, Baharan Mirzasoleiman, Andreas Krause, Yaron Singer |
| 2016 | Learning and Inference via Maximum Inner Product Search. Stephen Mussmann, Stefano Ermon |
| 2016 | Learning from Multiway Data: Simple and Efficient Tensor Regression. Rose Yu, Yan Liu |
| 2016 | Learning privately from multiparty data. Jihun Hamm, Yingjun Cao, Mikhail Belkin |
| 2016 | Learning to Filter with Predictive State Inference Machines. Wen Sun, Arun Venkatraman, Byron Boots, J. Andrew Bagnell |
| 2016 | Learning to Generate with Memory. Chongxuan Li, Jun Zhu, Bo Zhang |
| 2016 | Linking losses for density ratio and class-probability estimation. Aditya Krishna Menon, Cheng Soon Ong |
| 2016 | Loss factorization, weakly supervised learning and label noise robustness. Giorgio Patrini, Frank Nielsen, Richard Nock, Marcello Carioni |
| 2016 | Low-Rank Matrix Approximation with Stability. Dongsheng Li, Chao Chen, Qin Lv, Junchi Yan, Li Shang, Stephen M. Chu |
| 2016 | Low-rank Solutions of Linear Matrix Equations via Procrustes Flow. Stephen Tu, Ross Boczar, Max Simchowitz, Mahdi Soltanolkotabi, Ben Recht |
| 2016 | Low-rank tensor completion: a Riemannian manifold preconditioning approach. Hiroyuki Kasai, Bamdev Mishra |
| 2016 | Markov Latent Feature Models. Aonan Zhang, John W. Paisley |
| 2016 | Markov-modulated Marked Poisson Processes for Check-in Data. Jiangwei Pan, Vinayak A. Rao, Pankaj K. Agarwal, Alan E. Gelfand |
| 2016 | Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization. Zhiqiang Xu, Peilin Zhao, Jianneng Cao, Xiaoli Li |
| 2016 | Meta-Gradient Boosted Decision Tree Model for Weight and Target Learning. Yury Ustinovskiy, Valentina Fedorova, Gleb Gusev, Pavel Serdyukov |
| 2016 | Meta-Learning with Memory-Augmented Neural Networks. Adam Santoro, Sergey Bartunov, Matthew M. Botvinick, Daan Wierstra, Timothy P. Lillicrap |
| 2016 | Metadata-conscious anonymous messaging. Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, Pramod Viswanath |
| 2016 | Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs. Anton Osokin, Jean-Baptiste Alayrac, Isabella Lukasewitz, Puneet Kumar Dokania, Simon Lacoste-Julien |
| 2016 | Minimizing the Maximal Loss: How and Why. Shai Shalev-Shwartz, Yonatan Wexler |
| 2016 | Minimum Regret Search for Single- and Multi-Task Optimization. Jan Hendrik Metzen |
| 2016 | Mixing Rates for the Alternating Gibbs Sampler over Restricted Boltzmann Machines and Friends. Christopher Tosh |
| 2016 | Mixture Proportion Estimation via Kernel Embeddings of Distributions. Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari |
| 2016 | Model-Free Imitation Learning with Policy Optimization. Jonathan Ho, Jayesh K. Gupta, Stefano Ermon |
| 2016 | Model-Free Trajectory Optimization for Reinforcement Learning. Riad Akrour, Gerhard Neumann, Hany Abdulsamad, Abbas Abdolmaleki |
| 2016 | Multi-Bias Non-linear Activation in Deep Neural Networks. Hongyang Li, Wanli Ouyang, Xiaogang Wang |
| 2016 | Multi-Player Bandits - a Musical Chairs Approach. Jonathan Rosenski, Ohad Shamir, Liran Szlak |
| 2016 | Near Optimal Behavior via Approximate State Abstraction. David Abel, D. Ellis Hershkowitz, Michael L. Littman |
| 2016 | Network Morphism. Tao Wei, Changhu Wang, Yong Rui, Chang Wen Chen |
| 2016 | Neural Variational Inference for Text Processing. Yishu Miao, Lei Yu, Phil Blunsom |
| 2016 | No Oops, You Won't Do It Again: Mechanisms for Self-correction in Crowdsourcing. Nihar B. Shah, Dengyong Zhou |
| 2016 | No penalty no tears: Least squares in high-dimensional linear models. Xiangyu Wang, David B. Dunson, Chenlei Leng |
| 2016 | No-Regret Algorithms for Heavy-Tailed Linear Bandits. Andres Muñoz Medina, Scott Yang |
| 2016 | Noisy Activation Functions. Çaglar Gülçehre, Marcin Moczulski, Misha Denil, Yoshua Bengio |
| 2016 | Non-negative Matrix Factorization under Heavy Noise. Chiranjib Bhattacharyya, Navin Goyal, Ravindran Kannan, Jagdeep Pani |
| 2016 | Nonlinear Statistical Learning with Truncated Gaussian Graphical Models. Qinliang Su, Xuejun Liao, Changyou Chen, Lawrence Carin |
| 2016 | Nonparametric Canonical Correlation Analysis. Tomer Michaeli, Weiran Wang, Karen Livescu |
| 2016 | Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks. Devansh Arpit, Yingbo Zhou, Bhargava Urala Kota, Venu Govindaraju |
| 2016 | On Graduated Optimization for Stochastic Non-Convex Problems. Elad Hazan, Kfir Yehuda Levy, Shai Shalev-Shwartz |
| 2016 | On collapsed representation of hierarchical Completely Random Measures. Gaurav Pandey, Ambedkar Dukkipati |
| 2016 | On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search. Piyush Khandelwal, Elad Liebman, Scott Niekum, Peter Stone |
| 2016 | On the Consistency of Feature Selection With Lasso for Non-linear Targets. Yue Zhang, Weihong Guo, Soumya Ray |
| 2016 | On the Iteration Complexity of Oblivious First-Order Optimization Algorithms. Yossi Arjevani, Ohad Shamir |
| 2016 | On the Power and Limits of Distance-Based Learning. Periklis A. Papakonstantinou, Jia Xu, Guang Yang |
| 2016 | On the Quality of the Initial Basin in Overspecified Neural Networks. Itay Safran, Ohad Shamir |
| 2016 | On the Statistical Limits of Convex Relaxations. Zhaoran Wang, Quanquan Gu, Han Liu |
| 2016 | One-Shot Generalization in Deep Generative Models. Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra |
| 2016 | Online Learning with Feedback Graphs Without the Graphs. Alon Cohen, Tamir Hazan, Tomer Koren |
| 2016 | Online Low-Rank Subspace Clustering by Basis Dictionary Pursuit. Jie Shen, Ping Li, Huan Xu |
| 2016 | Online Stochastic Linear Optimization under One-bit Feedback. Lijun Zhang, Tianbao Yang, Rong Jin, Yichi Xiao, Zhi-Hua Zhou |
| 2016 | Opponent Modeling in Deep Reinforcement Learning. He He, Jordan L. Boyd-Graber |
| 2016 | Optimal Classification with Multivariate Losses. Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar, Inderjit S. Dhillon |
| 2016 | Optimality of Belief Propagation for Crowdsourced Classification. Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yung Yi |
| 2016 | PAC Lower Bounds and Efficient Algorithms for The Max \(K\)-Armed Bandit Problem. Yahel David, Nahum Shimkin |
| 2016 | PAC learning of Probabilistic Automaton based on the Method of Moments. Hadrien Glaude, Olivier Pietquin |
| 2016 | PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification. Ian En-Hsu Yen, Xiangru Huang, Pradeep Ravikumar, Kai Zhong, Inderjit S. Dhillon |
| 2016 | PHOG: Probabilistic Model for Code. Pavol Bielik, Veselin Raychev, Martin T. Vechev |
| 2016 | Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms. Yu-Xiang Wang, Veeranjaneyulu Sadhanala, Wei Dai, Willie Neiswanger, Suvrit Sra, Eric P. Xing |
| 2016 | Parameter Estimation for Generalized Thurstone Choice Models. Milan Vojnovic, Se-Young Yun |
| 2016 | Pareto Frontier Learning with Expensive Correlated Objectives. Amar Shah, Zoubin Ghahramani |
| 2016 | Partition Functions from Rao-Blackwellized Tempered Sampling. David E. Carlson, Patrick Stinson, Ari Pakman, Liam Paninski |
| 2016 | Persistence weighted Gaussian kernel for topological data analysis. Genki Kusano, Yasuaki Hiraoka, Kenji Fukumizu |
| 2016 | Persistent RNNs: Stashing Recurrent Weights On-Chip. Greg Diamos, Shubho Sengupta, Bryan Catanzaro, Mike Chrzanowski, Adam Coates, Erich Elsen, Jesse H. Engel, Awni Y. Hannun, Sanjeev Satheesh |
| 2016 | Pixel Recurrent Neural Networks. Aäron van den Oord, Nal Kalchbrenner, Koray Kavukcuoglu |
| 2016 | Pliable Rejection Sampling. Akram Erraqabi, Michal Valko, Alexandra Carpentier, Odalric-Ambrym Maillard |
| 2016 | Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms. Mathieu Blondel, Masakazu Ishihata, Akinori Fujino, Naonori Ueda |
| 2016 | Power of Ordered Hypothesis Testing. Lihua Lei, William Fithian |
| 2016 | Preconditioning Kernel Matrices. Kurt Cutajar, Michael A. Osborne, John P. Cunningham, Maurizio Filippone |
| 2016 | Predictive Entropy Search for Multi-objective Bayesian Optimization. Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Amar Shah, Ryan P. Adams |
| 2016 | Pricing a Low-regret Seller. Hoda Heidari, Mohammad Mahdian, Umar Syed, Sergei Vassilvitskii, Sadra Yazdanbod |
| 2016 | Primal-Dual Rates and Certificates. Celestine Dünner, Simone Forte, Martin Takác, Martin Jaggi |
| 2016 | Principal Component Projection Without Principal Component Analysis. Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford |
| 2016 | Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016 Maria-Florina Balcan, Kilian Q. Weinberger |
| 2016 | Provable Algorithms for Inference in Topic Models. Sanjeev Arora, Rong Ge, Frederic Koehler, Tengyu Ma, Ankur Moitra |
| 2016 | Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow. Huishuai Zhang, Yuejie Chi, Yingbin Liang |
| 2016 | Quadratic Optimization with Orthogonality Constraints: Explicit Lojasiewicz Exponent and Linear Convergence of Line-Search Methods. Huikang Liu, Weijie Wu, Anthony Man-Cho So |
| 2016 | Recommendations as Treatments: Debiasing Learning and Evaluation. Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, Thorsten Joachims |
| 2016 | Recovery guarantee of weighted low-rank approximation via alternating minimization. Yuanzhi Li, Yingyu Liang, Andrej Risteski |
| 2016 | Recurrent Orthogonal Networks and Long-Memory Tasks. Mikael Henaff, Arthur Szlam, Yann LeCun |
| 2016 | Recycling Randomness with Structure for Sublinear time Kernel Expansions. Krzysztof Choromanski, Vikas Sindhwani |
| 2016 | Representational Similarity Learning with Application to Brain Networks. Urvashi Oswal, Christopher R. Cox, Matthew A. Lambon Ralph, Timothy T. Rogers, Robert D. Nowak |
| 2016 | Revisiting Semi-Supervised Learning with Graph Embeddings. Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov |
| 2016 | Rich Component Analysis. Rong Ge, James Zou |
| 2016 | Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics. Anirban Roychowdhury, Brian Kulis, Srinivasan Parthasarathy |
| 2016 | Robust Principal Component Analysis with Side Information. Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon |
| 2016 | Robust Random Cut Forest Based Anomaly Detection on Streams. Sudipto Guha, Nina Mishra, Gourav Roy, Okke Schrijvers |
| 2016 | SDCA without Duality, Regularization, and Individual Convexity. Shai Shalev-Shwartz |
| 2016 | SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization. Zheng Qu, Peter Richtárik, Martin Takác, Olivier Fercoq |
| 2016 | Scalable Discrete Sampling as a Multi-Armed Bandit Problem. Yutian Chen, Zoubin Ghahramani |
| 2016 | Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters. Jelena Luketina, Tapani Raiko, Mathias Berglund, Klaus Greff |
| 2016 | Sequence to Sequence Training of CTC-RNNs with Partial Windowing. Kyuyeon Hwang, Wonyong Sung |
| 2016 | Shifting Regret, Mirror Descent, and Matrices. András György, Csaba Szepesvári |
| 2016 | Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling. Atsushi Shibagaki, Masayuki Karasuyama, Kohei Hatano, Ichiro Takeuchi |
| 2016 | Slice Sampling on Hamiltonian Trajectories. Benjamin Bloem-Reddy, John P. Cunningham |
| 2016 | Smooth Imitation Learning for Online Sequence Prediction. Hoang Minh Le, Andrew Kang, Yisong Yue, Peter Carr |
| 2016 | Softened Approximate Policy Iteration for Markov Games. Julien Pérolat, Bilal Piot, Matthieu Geist, Bruno Scherrer, Olivier Pietquin |
| 2016 | Solving Ridge Regression using Sketched Preconditioned SVRG. Alon Gonen, Francesco Orabona, Shai Shalev-Shwartz |
| 2016 | Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity. Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina C. Eldar, Tong Zhang |
| 2016 | Sparse Parameter Recovery from Aggregated Data. Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo |
| 2016 | Speeding up k-means by approximating Euclidean distances via block vectors. Thomas Bottesch, Thomas Bühler, Markus Kächele |
| 2016 | Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies. David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon |
| 2016 | Stability of Controllers for Gaussian Process Forward Models. Julia Vinogradska, Bastian Bischoff, Duy Nguyen-Tuong, Anne Romer, Henner Schmidt, Jan Peters |
| 2016 | Starting Small - Learning with Adaptive Sample Sizes. Hadi Daneshmand, Aurélien Lucchi, Thomas Hofmann |
| 2016 | Stochastic Block BFGS: Squeezing More Curvature out of Data. Robert M. Gower, Donald Goldfarb, Peter Richtárik |
| 2016 | Stochastic Discrete Clenshaw-Curtis Quadrature. Nico Piatkowski, Katharina Morik |
| 2016 | Stochastic Optimization for Multiview Representation Learning using Partial Least Squares. Raman Arora, Poorya Mianjy, Teodor V. Marinov |
| 2016 | Stochastic Quasi-Newton Langevin Monte Carlo. Umut Simsekli, Roland Badeau, A. Taylan Cemgil, Gaël Richard |
| 2016 | Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt |
| 2016 | Stochastic Variance Reduction for Nonconvex Optimization. Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabás Póczos, Alexander J. Smola |
| 2016 | Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues. Nihar B. Shah, Sivaraman Balakrishnan, Aditya Guntuboyina, Martin J. Wainwright |
| 2016 | Stratified Sampling Meets Machine Learning. Edo Liberty, Kevin J. Lang, Konstantin Shmakov |
| 2016 | Strongly-Typed Recurrent Neural Networks. David Balduzzi, Muhammad Ghifary |
| 2016 | Structure Learning of Partitioned Markov Networks. Song Liu, Taiji Suzuki, Masashi Sugiyama, Kenji Fukumizu |
| 2016 | Structured Prediction Energy Networks. David Belanger, Andrew McCallum |
| 2016 | Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors. Christos Louizos, Max Welling |
| 2016 | Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings. Rie Johnson, Tong Zhang |
| 2016 | Tensor Decomposition via Joint Matrix Schur Decomposition. Nicolò Colombo, Nikos Vlassis |
| 2016 | Texture Networks: Feed-forward Synthesis of Textures and Stylized Images. Dmitry Ulyanov, Vadim Lebedev, Andrea Vedaldi, Victor S. Lempitsky |
| 2016 | The Arrow of Time in Multivariate Time Series. Stefan Bauer, Bernhard Schölkopf, Jonas Peters |
| 2016 | The Information Sieve. Greg Ver Steeg, Aram Galstyan |
| 2016 | The Information-Theoretic Requirements of Subspace Clustering with Missing Data. Daniel L. Pimentel-Alarcón, Robert D. Nowak |
| 2016 | The Knowledge Gradient for Sequential Decision Making with Stochastic Binary Feedbacks. Yingfei Wang, Chu Wang, Warren B. Powell |
| 2016 | The Label Complexity of Mixed-Initiative Classifier Training. Jina Suh, Xiaojin Zhu, Saleema Amershi |
| 2016 | The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM. Ardavan Saeedi, Matthew D. Hoffman, Matthew J. Johnson, Ryan P. Adams |
| 2016 | The Sum-Product Theorem: A Foundation for Learning Tractable Models. Abram L. Friesen, Pedro M. Domingos |
| 2016 | The Teaching Dimension of Linear Learners. Ji Liu, Xiaojin Zhu, Hrag Ohannessian |
| 2016 | The Variational Nystrom method for large-scale spectral problems. Max Vladymyrov, Miguel Á. Carreira-Perpiñán |
| 2016 | The knockoff filter for FDR control in group-sparse and multitask regression. Ran Dai, Rina Barber |
| 2016 | Towards Faster Rates and Oracle Property for Low-Rank Matrix Estimation. Huan Gui, Jiawei Han, Quanquan Gu |
| 2016 | Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient. Tianbao Yang, Lijun Zhang, Rong Jin, Jinfeng Yi |
| 2016 | Train and Test Tightness of LP Relaxations in Structured Prediction. Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David A. Sontag |
| 2016 | Train faster, generalize better: Stability of stochastic gradient descent. Moritz Hardt, Ben Recht, Yoram Singer |
| 2016 | Training Deep Neural Networks via Direct Loss Minimization. Yang Song, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun |
| 2016 | Training Neural Networks Without Gradients: A Scalable ADMM Approach. Gavin Taylor, Ryan Burmeister, Zheng Xu, Bharat Singh, Ankit B. Patel, Tom Goldstein |
| 2016 | Truthful Univariate Estimators. Ioannis Caragiannis, Ariel D. Procaccia, Nisarg Shah |
| 2016 | Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units. Wenling Shang, Kihyuk Sohn, Diogo Almeida, Honglak Lee |
| 2016 | Unitary Evolution Recurrent Neural Networks. Martín Arjovsky, Amar Shah, Yoshua Bengio |
| 2016 | Unsupervised Deep Embedding for Clustering Analysis. Junyuan Xie, Ross B. Girshick, Ali Farhadi |
| 2016 | Uprooting and Rerooting Graphical Models. Adrian Weller |
| 2016 | Variable Elimination in the Fourier Domain. Yexiang Xue, Stefano Ermon, Ronan Le Bras, Carla P. Gomes, Bart Selman |
| 2016 | Variance Reduction for Faster Non-Convex Optimization. Zeyuan Allen Zhu, Elad Hazan |
| 2016 | Variance-Reduced and Projection-Free Stochastic Optimization. Elad Hazan, Haipeng Luo |
| 2016 | Variational Inference for Monte Carlo Objectives. Andriy Mnih, Danilo Jimenez Rezende |
| 2016 | Why Most Decisions Are Easy in Tetris - And Perhaps in Other Sequential Decision Problems, As Well. Özgür Simsek, Simón Algorta, Amit Kothiyal |
| 2016 | Why Regularized Auto-Encoders learn Sparse Representation? Devansh Arpit, Yingbo Zhou, Hung Q. Ngo, Venu Govindaraju |
| 2016 | k-variates++: more pluses in the k-means++. Richard Nock, Raphaël Canyasse, Roksana Boreli, Frank Nielsen |