| 2016 | (Bandit) Convex Optimization with Biased Noisy Gradient Oracles. Xiaowei Hu, Prashanth L. A., András György, Csaba Szepesvári |
| 2016 | A Column Generation Bound Minimization Approach with PAC-Bayesian Generalization Guarantees. Jean-Francis Roy, Mario Marchand, François Laviolette |
| 2016 | A Convex Surrogate Operator for General Non-Modular Loss Functions. Jiaqian Yu, Matthew B. Blaschko |
| 2016 | A Deep Generative Deconvolutional Image Model. Yunchen Pu, Xin Yuan, Andrew Stevens, Chunyuan Li, Lawrence Carin |
| 2016 | A Fast and Reliable Policy Improvement Algorithm. Yasin Abbasi-Yadkori, Peter L. Bartlett, Stephen J. Wright |
| 2016 | A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models. Rishit Sheth, Roni Khardon |
| 2016 | A Lasso-based Sparse Knowledge Gradient Policy for Sequential Optimal Learning. Yan Li, Han Liu, Warren B. Powell |
| 2016 | A Linearly-Convergent Stochastic L-BFGS Algorithm. Philipp Moritz, Robert Nishihara, Michael I. Jordan |
| 2016 | A PAC RL Algorithm for Episodic POMDPs. Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill |
| 2016 | A Robust-Equitable Copula Dependence Measure for Feature Selection. Yale Chang, Yi Li, A. Adam Ding, Jennifer G. Dy |
| 2016 | Accelerated Stochastic Gradient Descent for Minimizing Finite Sums. Atsushi Nitanda |
| 2016 | Accelerating Online Convex Optimization via Adaptive Prediction. Mehryar Mohri, Scott Yang |
| 2016 | Active Learning Algorithms for Graphical Model Selection. Gautam Dasarathy, Aarti Singh, Maria-Florina Balcan, Jong Hyuk Park |
| 2016 | AdaDelay: Delay Adaptive Distributed Stochastic Optimization. Suvrit Sra, Adams Wei Yu, Mu Li, Alexander J. Smola |
| 2016 | An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong |
| 2016 | Approximate Inference Using DC Programming For Collective Graphical Models. Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau, Daniel Sheldon |
| 2016 | Back to the Future: Radial Basis Function Networks Revisited. Qichao Que, Mikhail Belkin |
| 2016 | Batch Bayesian Optimization via Local Penalization. Javier González, Zhenwen Dai, Philipp Hennig, Neil D. Lawrence |
| 2016 | Bayes-Optimal Effort Allocation in Crowdsourcing: Bounds and Index Policies. Weici Hu, Peter I. Frazier |
| 2016 | Bayesian Generalised Ensemble Markov Chain Monte Carlo. Jes Frellsen, Ole Winther, Zoubin Ghahramani, Jesper Ferkinghoff-Borg |
| 2016 | Bayesian Markov Blanket Estimation. Dinu Kaufmann, Sonali Parbhoo, Aleksander Wieczorek, Sebastian Keller, David Adametz, Volker Roth |
| 2016 | Bayesian Nonparametric Kernel-Learning. Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing |
| 2016 | Bethe Learning of Graphical Models via MAP Decoding. Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara |
| 2016 | Bipartite Correlation Clustering: Maximizing Agreements. Megasthenis Asteris, Anastasios Kyrillidis, Dimitris S. Papailiopoulos, Alexandros G. Dimakis |
| 2016 | Black-Box Policy Search with Probabilistic Programs. Jan-Willem van de Meent, Brooks Paige, David Tolpin, Frank D. Wood |
| 2016 | Breaking Sticks and Ambiguities with Adaptive Skip-gram. Sergey Bartunov, Dmitry Kondrashkin, Anton Osokin, Dmitry P. Vetrov |
| 2016 | Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization. Changyou Chen, David E. Carlson, Zhe Gan, Chunyuan Li, Lawrence Carin |
| 2016 | C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching. Daniel Ritchie, Andreas Stuhlmüller, Noah D. Goodman |
| 2016 | CRAFT: ClusteR-specific Assorted Feature selecTion. Vikas K. Garg, Cynthia Rudin, Tommi S. Jaakkola |
| 2016 | Chained Gaussian Processes. Alan D. Saul, James Hensman, Aki Vehtari, Neil D. Lawrence |
| 2016 | Clamping Improves TRW and Mean Field Approximations. Adrian Weller, Justin Domke |
| 2016 | Communication Efficient Distributed Agnostic Boosting. Shang-Tse Chen, Maria-Florina Balcan, Duen Horng Chau |
| 2016 | Computationally Efficient Bayesian Learning of Gaussian Process State Space Models. Andreas Svensson, Arno Solin, Simo Särkkä, Thomas B. Schön |
| 2016 | Consistently Estimating Markov Chains with Noisy Aggregate Data. Garrett Bernstein, Daniel Sheldon |
| 2016 | Control Functionals for Quasi-Monte Carlo Integration. Chris J. Oates, Mark A. Girolami |
| 2016 | Controlling Bias in Adaptive Data Analysis Using Information Theory. Daniel Russo, James Zou |
| 2016 | Convex Block-sparse Linear Regression with Expanders - Provably. Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher |
| 2016 | Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions. Loïc Landrieu, Guillaume Obozinski |
| 2016 | DUAL-LOCO: Distributing Statistical Estimation Using Random Projections. Christina Heinze, Brian McWilliams, Nicolai Meinshausen |
| 2016 | Deep Kernel Learning. Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing |
| 2016 | Determinantal Regularization for Ensemble Variable Selection. Veronika Rocková, Gemma E. Moran, Edward I. George |
| 2016 | Discriminative Structure Learning of Arithmetic Circuits. Amirmohammad Rooshenas, Daniel Lowd |
| 2016 | Distributed Multi-Task Learning. Jialei Wang, Mladen Kolar, Nathan Srebro |
| 2016 | Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation. Søren Hauberg, Oren Freifeld, Anders Boesen Lindbo Larsen, John W. Fisher III, Lars Kai Hansen |
| 2016 | Early Stopping as Nonparametric Variational Inference. David Duvenaud, Dougal Maclaurin, Ryan P. Adams |
| 2016 | Efficient Bregman Projections onto the Permutahedron and Related Polytopes. Cong Han Lim, Stephen J. Wright |
| 2016 | Efficient Sampling for k-Determinantal Point Processes. Chengtao Li, Stefanie Jegelka, Suvrit Sra |
| 2016 | Enumerating Equivalence Classes of Bayesian Networks using EC Graphs. Eunice Yuh-Jie Chen, Arthur Choi, Adnan Darwiche |
| 2016 | Exponential Stochastic Cellular Automata for Massively Parallel Inference. Manzil Zaheer, Michael L. Wick, Jean-Baptiste Tristan, Alexander J. Smola, Guy L. Steele Jr. |
| 2016 | Fast Convergence of Online Pairwise Learning Algorithms. Martin Boissier, Siwei Lyu, Yiming Ying, Ding-Xuan Zhou |
| 2016 | Fast Dictionary Learning with a Smoothed Wasserstein Loss. Antoine Rolet, Marco Cuturi, Gabriel Peyré |
| 2016 | Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm. Sangkyun Lee, Damian Brzyski, Malgorzata Bogdan |
| 2016 | Fast and Scalable Structural SVM with Slack Rescaling. Heejin Choi, Ofer Meshi, Nathan Srebro |
| 2016 | Fitting Spectral Decay with the k-Support Norm. Andrew M. McDonald, Massimiliano Pontil, Dimitris Stamos |
| 2016 | GLASSES: Relieving The Myopia Of Bayesian Optimisation. Javier González, Michael A. Osborne, Neil D. Lawrence |
| 2016 | Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables. Yaniv Tenzer, Gal Elidan |
| 2016 | Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree. Chen-Yu Lee, Patrick W. Gallagher, Zhuowen Tu |
| 2016 | Geometry Aware Mappings for High Dimensional Sparse Factors. Avradeep Bhowmik, Nathan Liu, Erheng Zhong, Badri Narayan Bhaskar, Suju Rajan |
| 2016 | Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation. Dejiao Zhang, Laura Balzano |
| 2016 | Globally Sparse Probabilistic PCA. Pierre-Alexandre Mattei, Charles Bouveyron, Pierre Latouche |
| 2016 | Graph Connectivity in Noisy Sparse Subspace Clustering. Yining Wang, Yu-Xiang Wang, Aarti Singh |
| 2016 | Graph Sparsification Approaches for Laplacian Smoothing. Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Ryan J. Tibshirani |
| 2016 | High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models. Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider |
| 2016 | How to Learn a Graph from Smooth Signals. Vassilis Kalofolias |
| 2016 | Improper Deep Kernels. Uri Heinemann, Roi Livni, Elad Eban, Gal Elidan, Amir Globerson |
| 2016 | Improved Learning Complexity in Combinatorial Pure Exploration Bandits. Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Ronald Ortner, Peter L. Bartlett |
| 2016 | Inference for High-dimensional Exponential Family Graphical Models. Jialei Wang, Mladen Kolar |
| 2016 | Inverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics. Michael Herman, Tobias Gindele, Jörg Wagner, Felix Schmitt, Wolfram Burgard |
| 2016 | K2-ABC: Approximate Bayesian Computation with Kernel Embeddings. Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic |
| 2016 | Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation. Sujith Ravi, Qiming Diao |
| 2016 | Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models. Calvin McCarter, Seyoung Kim |
| 2016 | Latent Point Process Allocation. Chris M. Lloyd, Tom Gunter, Michael A. Osborne, Stephen J. Roberts, Tom Nickson |
| 2016 | Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation. Sebastian Tschiatschek, Josip Djolonga, Andreas Krause |
| 2016 | Learning Relationships between Data Obtained Independently. Alexandra Carpentier, Teresa Schlueter |
| 2016 | Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization. Zhao Song, Ricardo Henao, David E. Carlson, Lawrence Carin |
| 2016 | Learning Sparse Additive Models with Interactions in High Dimensions. Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause |
| 2016 | Learning Structured Low-Rank Representation via Matrix Factorization. Jie Shen, Ping Li |
| 2016 | Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices. Jonathan Scarlett, Volkan Cevher |
| 2016 | Loss Bounds and Time Complexity for Speed Priors. Daniel Filan, Jan Leike, Marcus Hutter |
| 2016 | Low-Rank Approximation of Weighted Tree Automata. Guillaume Rabusseau, Borja Balle, Shay B. Cohen |
| 2016 | Low-Rank and Sparse Structure Pursuit via Alternating Minimization. Quanquan Gu, Zhaoran Wang, Han Liu |
| 2016 | Maximum Likelihood for Variance Estimation in High-Dimensional Linear Models. Lee H. Dicker, Murat A. Erdogdu |
| 2016 | Model-based Co-clustering for High Dimensional Sparse Data. Aghiles Salah, Nicoleta Rogovschi, Mohamed Nadif |
| 2016 | Mondrian Forests for Large-Scale Regression when Uncertainty Matters. Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh |
| 2016 | Multi-Level Cause-Effect Systems. Krzysztof Chalupka, Frederick Eberhardt, Pietro Perona |
| 2016 | Multiresolution Matrix Compression. Nedelina Teneva, Pramod Kaushik Mudrakarta, Risi Kondor |
| 2016 | NYTRO: When Subsampling Meets Early Stopping. Raffaello Camoriano, Tomás Angles, Alessandro Rudi, Lorenzo Rosasco |
| 2016 | Nearly Optimal Classification for Semimetrics. Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch |
| 2016 | New Resistance Distances with Global Information on Large Graphs. Canh Hao Nguyen, Hiroshi Mamitsuka |
| 2016 | No Regret Bound for Extreme Bandits. Robert Nishihara, David Lopez-Paz, Léon Bottou |
| 2016 | Non-Gaussian Component Analysis with Log-Density Gradient Estimation. Hiroaki Sasaki, Gang Niu, Masashi Sugiyama |
| 2016 | Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo. Markus Heinonen, Henrik Mannerström, Juho Rousu, Samuel Kaski, Harri Lähdesmäki |
| 2016 | Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information. Changwei Hu, Piyush Rai, Lawrence Carin |
| 2016 | Non-stochastic Best Arm Identification and Hyperparameter Optimization. Kevin Jamieson, Ameet Talwalkar |
| 2016 | Nonparametric Budgeted Stochastic Gradient Descent. Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung |
| 2016 | NuC-MKL: A Convex Approach to Non Linear Multiple Kernel Learning. Eli A. Meirom, Pavel Kisilev |
| 2016 | On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System. Yi Zhou, Yaoliang Yu, Wei Dai, Yingbin Liang, Eric P. Xing |
| 2016 | On Lloyd's Algorithm: New Theoretical Insights for Clustering in Practice. Cheng Tang, Claire Monteleoni |
| 2016 | On Searching for Generalized Instrumental Variables. Benito van der Zander, Maciej Liskiewicz |
| 2016 | On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes. Alexander G. de G. Matthews, James Hensman, Richard E. Turner, Zoubin Ghahramani |
| 2016 | On the Reducibility of Submodular Functions. Jincheng Mei, Hao Zhang, Bao-Liang Lu |
| 2016 | On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games. Julien Pérolat, Bilal Piot, Bruno Scherrer, Olivier Pietquin |
| 2016 | One Scan 1-Bit Compressed Sensing. Ping Li |
| 2016 | Online (and Offline) Robust PCA: Novel Algorithms and Performance Guarantees. Jinchun Zhan, Brian Lois, Han Guo, Namrata Vaswani |
| 2016 | Online Learning to Rank with Feedback at the Top. Sougata Chaudhuri, Ambuj Tewari |
| 2016 | Online Learning with Noisy Side Observations. Tomás Kocák, Gergely Neu, Michal Valko |
| 2016 | Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings. Zhitang Chen, Pascal Poupart, Yanhui Geng |
| 2016 | Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks. Abdullah Rashwan, Han Zhao, Pascal Poupart |
| 2016 | Optimal Statistical and Computational Rates for One Bit Matrix Completion. Renkun Ni, Quanquan Gu |
| 2016 | Optimization as Estimation with Gaussian Processes in Bandit Settings. Zi Wang, Bolei Zhou, Stefanie Jegelka |
| 2016 | Ordered Weighted L1 Regularized Regression with Strongly Correlated Covariates: Theoretical Aspects. Mário A. T. Figueiredo, Robert D. Nowak |
| 2016 | PAC-Bayesian Bounds based on the Rényi Divergence. Luc Bégin, Pascal Germain, François Laviolette, Jean-Francis Roy |
| 2016 | Parallel Majorization Minimization with Dynamically Restricted Domains for Nonconvex Optimization. Yan Kaganovsky, Ikenna Odinaka, David E. Carlson, Lawrence Carin |
| 2016 | Parallel Markov Chain Monte Carlo via Spectral Clustering. Guillaume W. Basse, Aaron Smith, Natesh S. Pillai |
| 2016 | Pareto Front Identification from Stochastic Bandit Feedback. Peter Auer, Chao-Kai Chiang, Ronald Ortner, Madalina M. Drugan |
| 2016 | Precision Matrix Estimation in High Dimensional Gaussian Graphical Models with Faster Rates. Lingxiao Wang, Xiang Ren, Quanquan Gu |
| 2016 | Private Causal Inference. Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger |
| 2016 | Probabilistic Approximate Least-Squares. Simon Bartels, Philipp Hennig |
| 2016 | Probability Inequalities for Kernel Embeddings in Sampling without Replacement. Markus Schneider |
| 2016 | Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, AISTATS 2016, Cadiz, Spain, May 9-11, 2016 Arthur Gretton, Christian C. Robert |
| 2016 | Provable Bayesian Inference via Particle Mirror Descent. Bo Dai, Niao He, Hanjun Dai, Le Song |
| 2016 | Provable Tensor Methods for Learning Mixtures of Generalized Linear Models. Hanie Sedghi, Majid Janzamin, Anima Anandkumar |
| 2016 | Pseudo-Marginal Slice Sampling. Iain Murray, Matthew M. Graham |
| 2016 | Quantization based Fast Inner Product Search. Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski, David Simcha |
| 2016 | Random Forest for the Contextual Bandit Problem. Raphaël Féraud, Robin Allesiardo, Tanguy Urvoy, Fabrice Clérot |
| 2016 | Randomization and The Pernicious Effects of Limited Budgets on Auction Experiments. Guillaume W. Basse, Hossein Azari Soufiani, Diane Lambert |
| 2016 | Relationship between PreTraining and Maximum Likelihood Estimation in Deep Boltzmann Machines. Muneki Yasuda |
| 2016 | Revealing Graph Bandits for Maximizing Local Influence. Alexandra Carpentier, Michal Valko |
| 2016 | Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu |
| 2016 | Robust Covariate Shift Regression. Xiangli Chen, Mathew Monfort, Anqi Liu, Brian D. Ziebart |
| 2016 | Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation. Ian En-Hsu Yen, Dmitry Malioutov, Abhishek Kumar |
| 2016 | Scalable Gaussian Process Classification via Expectation Propagation. Daniel Hernández-Lobato, José Miguel Hernández-Lobato |
| 2016 | Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces. William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth R. Flaxman, Daniel B. Neill, Wilbert Van Panhuis, Eric P. Xing |
| 2016 | Scalable MCMC for Mixed Membership Stochastic Blockmodels. Wenzhe Li, Sungjin Ahn, Max Welling |
| 2016 | Scalable and Sound Low-Rank Tensor Learning. Hao Cheng, Yaoliang Yu, Xinhua Zhang, Eric P. Xing, Dale Schuurmans |
| 2016 | Scalable geometric density estimation. Ye Wang, Antonio Canale, David B. Dunson |
| 2016 | Score Permutation Based Finite Sample Inference for Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Models. Balázs Csanád Csáji |
| 2016 | Semi-Supervised Learning with Adaptive Spectral Transform. Hanxiao Liu, Yiming Yang |
| 2016 | Sequential Inference for Deep Gaussian Process. Yali Wang, Marcus A. Brubaker, Brahim Chaib-draa, Raquel Urtasun |
| 2016 | Simple and Scalable Constrained Clustering: a Generalized Spectral Method. Mihai Cucuringu, Ioannis Koutis, Sanjay Chawla, Gary L. Miller, Richard Peng |
| 2016 | Sketching, Embedding and Dimensionality Reduction in Information Theoretic Spaces. Amirali Abdullah, Ravi Kumar, Andrew McGregor, Sergei Vassilvitskii, Suresh Venkatasubramanian |
| 2016 | Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking. Nicolas Goix, Anne Sabourin, Stéphan Clémençon |
| 2016 | Spectral M-estimation with Applications to Hidden Markov Models. Dustin Tran, Minjae Kim, Finale Doshi-Velez |
| 2016 | Stochastic Neural Networks with Monotonic Activation Functions. Siamak Ravanbakhsh, Barnabás Póczos, Jeff G. Schneider, Dale Schuurmans, Russell Greiner |
| 2016 | Stochastic Variational Inference for the HDP-HMM. Aonan Zhang, San Gultekin, John W. Paisley |
| 2016 | Streaming Kernel Principal Component Analysis. Mina Ghashami, Daniel J. Perry, Jeff M. Phillips |
| 2016 | Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. Mario Lucic, Olivier Bachem, Andreas Krause |
| 2016 | Supervised Neighborhoods for Distributed Nonparametric Regression. Adam E. Bloniarz, Ameet Talwalkar, Bin Yu, Christopher Wu |
| 2016 | Survey Propagation beyond Constraint Satisfaction Problems. Christopher Srinivasa, Siamak Ravanbakhsh, Brendan J. Frey |
| 2016 | Tensor vs. Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations. Anima Anandkumar, Prateek Jain, Yang Shi, U. N. Niranjan |
| 2016 | The Nonparametric Kernel Bayes Smoother. Yu Nishiyama, Amir Afsharinejad, Shunsuke Naruse, Byron Boots, Le Song |
| 2016 | Tight Variational Bounds via Random Projections and I-Projections. Lun-Kai Hsu, Tudor Achim, Stefano Ermon |
| 2016 | Tightness of LP Relaxations for Almost Balanced Models. Adrian Weller, Mark Rowland, David A. Sontag |
| 2016 | Time-Varying Gaussian Process Bandit Optimization. Ilija Bogunovic, Jonathan Scarlett, Volkan Cevher |
| 2016 | Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls. Kwang-Sung Jun, Kevin Jamieson, Robert D. Nowak, Xiaojin Zhu |
| 2016 | Topic-Based Embeddings for Learning from Large Knowledge Graphs. Changwei Hu, Piyush Rai, Lawrence Carin |
| 2016 | Towards Stability and Optimality in Stochastic Gradient Descent. Panos Toulis, Dustin Tran, Edoardo M. Airoldi |
| 2016 | Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. Fanhua Shang, Yuanyuan Liu, James Cheng |
| 2016 | Unbounded Bayesian Optimization via Regularization. Bobak Shahriari, Alexandre Bouchard-Côté, Nando de Freitas |
| 2016 | Universal Models of Multivariate Temporal Point Processes. Asela Gunawardana, Christopher Meek |
| 2016 | Unsupervised Ensemble Learning with Dependent Classifiers. Ariel Jaffe, Ethan Fetaya, Boaz Nadler, Tingting Jiang, Yuval Kluger |
| 2016 | Unsupervised Feature Selection by Preserving Stochastic Neighbors. Xiaokai Wei, Philip S. Yu |
| 2016 | Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction. Tom Goldstein, Gavin Taylor, Kawika Barabin, Kent Sayre |
| 2016 | Variational Gaussian Copula Inference. Shaobo Han, Xuejun Liao, David B. Dunson, Lawrence Carin |
| 2016 | Variational Tempering. Stephan Mandt, James McInerney, Farhan Abrol, Rajesh Ranganath, David M. Blei |