| 2017 | A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models. Beilun Wang, Ji Gao, Yanjun Qi |
| 2017 | A Framework for Optimal Matching for Causal Inference. Nathan Kallus |
| 2017 | A Learning Theory of Ranking Aggregation. Anna Korba, Stéphan Clémençon, Eric Sibony |
| 2017 | A Lower Bound on the Partition Function of Attractive Graphical Models in the Continuous Case. Nicholas Ruozzi |
| 2017 | A Maximum Matching Algorithm for Basis Selection in Spectral Learning. Ariadna Quattoni, Xavier Carreras, Matthias Gallé |
| 2017 | A New Class of Private Chi-Square Hypothesis Tests. Ryan Rogers, Daniel Kifer |
| 2017 | A Stochastic Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization. Songtao Lu, Mingyi Hong, Zhengdao Wang |
| 2017 | A Sub-Quadratic Exact Medoid Algorithm. James Newling, François Fleuret |
| 2017 | A Unified Computational and Statistical Framework for Nonconvex Low-rank Matrix Estimation. Lingxiao Wang, Xiao Zhang, Quanquan Gu |
| 2017 | A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe. Francesco Locatello, Rajiv Khanna, Michael Tschannen, Martin Jaggi |
| 2017 | ASAGA: Asynchronous Parallel SAGA. Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien |
| 2017 | Active Positive Semidefinite Matrix Completion: Algorithms, Theory and Applications. Aniruddha Bhargava, Ravi Ganti, Robert D. Nowak |
| 2017 | Adaptive ADMM with Spectral Penalty Parameter Selection. Zheng Xu, Mário A. T. Figueiredo, Tom Goldstein |
| 2017 | An Information-Theoretic Route from Generalization in Expectation to Generalization in Probability. Ibrahim M. Alabdulmohsin |
| 2017 | Annular Augmentation Sampling. Francois Fagan, Jalaj Bhandari, John P. Cunningham |
| 2017 | Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere. Albert Thomas, Stéphan Clémençon, Alexandre Gramfort, Anne Sabourin |
| 2017 | Asymptotically exact inference in differentiable generative models. Matthew M. Graham, Amos J. Storkey |
| 2017 | Attributing Hacks. Ziqi Liu, Alexander J. Smola, Kyle Soska, Yu-Xiang Wang, Qinghua Zheng |
| 2017 | Automated Inference with Adaptive Batches. Soham De, Abhay Kumar Yadav, David W. Jacobs, Tom Goldstein |
| 2017 | Bayesian Hybrid Matrix Factorisation for Data Integration. Thomas Brouwer, Pietro Liò |
| 2017 | Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems. Scott W. Linderman, Matthew J. Johnson, Andrew C. Miller, Ryan P. Adams, David M. Blei, Liam Paninski |
| 2017 | Belief Propagation in Conditional RBMs for Structured Prediction. Wei Ping, Alexander Ihler |
| 2017 | Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers. Meelis Kull, Telmo de Menezes e Silva Filho, Peter A. Flach |
| 2017 | Binary and Multi-Bit Coding for Stable Random Projections. Ping Li |
| 2017 | Black-box Importance Sampling. Qiang Liu, Jason D. Lee |
| 2017 | CPSG-MCMC: Clustering-Based Preprocessing method for Stochastic Gradient MCMC. Tianfan Fu, Zhihua Zhang |
| 2017 | Clustering from Multiple Uncertain Experts. Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy |
| 2017 | Co-Occurring Directions Sketching for Approximate Matrix Multiply. Youssef Mroueh, Etienne Marcheret, Vaibhava Goel |
| 2017 | Combinatorial Topic Models using Small-Variance Asymptotics. Ke Jiang, Suvrit Sra, Brian Kulis |
| 2017 | Communication-Efficient Learning of Deep Networks from Decentralized Data. Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, Blaise Agüera y Arcas |
| 2017 | Communication-efficient Distributed Sparse Linear Discriminant Analysis. Lu Tian, Quanquan Gu |
| 2017 | Comparison-Based Nearest Neighbor Search. Siavash Haghiri, Debarghya Ghoshdastidar, Ulrike von Luxburg |
| 2017 | Complementary Sum Sampling for Likelihood Approximation in Large Scale Classification. Aleksandar Botev, Bowen Zheng, David Barber |
| 2017 | Compressed Least Squares Regression revisited. Martin Slawski |
| 2017 | Conditions beyond treewidth for tightness of higher-order LP relaxations. Mark Rowland, Aldo Pacchiano, Adrian Weller |
| 2017 | Conjugate-Computation Variational Inference: Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models. Mohammad Emtiyaz Khan, Wu Lin |
| 2017 | Consistent and Efficient Nonparametric Different-Feature Selection. Satoshi Hara, Takayuki Katsuki, Hiroki Yanagisawa, Takafumi Ono, Ryo Okamoto, Shigeki Takeuchi |
| 2017 | Contextual Bandits with Latent Confounders: An NMF Approach. Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai |
| 2017 | ConvNets with Smooth Adaptive Activation Functions for Regression. Le Hou, Dimitris Samaras, Tahsin M. Kurç, Yi Gao, Joel H. Saltz |
| 2017 | Convergence Rate of Stochastic k-means. Cheng Tang, Claire Monteleoni |
| 2017 | DP-EM: Differentially Private Expectation Maximization. Mijung Park, James R. Foulds, Kamalika Choudhary, Max Welling |
| 2017 | Data Driven Resource Allocation for Distributed Learning. Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Nina Balcan, Alexander J. Smola |
| 2017 | Decentralized Collaborative Learning of Personalized Models over Networks. Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi |
| 2017 | Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes. Feras Saad, Vikash Mansinghka |
| 2017 | Discovering and Exploiting Additive Structure for Bayesian Optimization. Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger B. Grosse |
| 2017 | Distance Covariance Analysis. Benjamin Cowley, João D. Semedo, Amin Zandvakili, Matthew A. Smith, Adam Kohn, Byron M. Yu |
| 2017 | Distributed Adaptive Sampling for Kernel Matrix Approximation. Daniele Calandriello, Alessandro Lazaric, Michal Valko |
| 2017 | Distribution of Gaussian Process Arc Lengths. Justin Bewsher, Alessandra Tosi, Michael A. Osborne, Stephen J. Roberts |
| 2017 | Diverse Neural Network Learns True Target Functions. Bo Xie, Yingyu Liang, Le Song |
| 2017 | Dynamic Collaborative Filtering With Compound Poisson Factorization. Ghassen Jerfel, Mehmet Emin Basbug, Barbara E. Engelhardt |
| 2017 | Efficient Algorithm for Sparse Tensor-variate Gaussian Graphical Models via Gradient Descent. Pan Xu, Tingting Zhang, Quanquan Gu |
| 2017 | Efficient Online Multiclass Prediction on Graphs via Surrogate Losses. Alexander Rakhlin, Karthik Sridharan |
| 2017 | Efficient Rank Aggregation via Lehmer Codes. Pan Li, Arya Mazumdar, Olgica Milenkovic |
| 2017 | Encrypted Accelerated Least Squares Regression. Pedro M. Esperança, Louis J. M. Aslett, Chris C. Holmes |
| 2017 | Estimating Density Ridges by Direct Estimation of Density-Derivative-Ratios. Hiroaki Sasaki, Takafumi Kanamori, Masashi Sugiyama |
| 2017 | Exploration-Exploitation in MDPs with Options. Ronan Fruit, Alessandro Lazaric |
| 2017 | Fairness Constraints: Mechanisms for Fair Classification. Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna P. Gummadi |
| 2017 | Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets. Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter |
| 2017 | Fast Classification with Binary Prototypes. Kai Zhong, Ruiqi Guo, Sanjiv Kumar, Bowei Yan, David Simcha, Inderjit S. Dhillon |
| 2017 | Fast column generation for atomic norm regularization. Marina Vinyes, Guillaume Obozinski |
| 2017 | Fast rates with high probability in exp-concave statistical learning. Nishant A. Mehta |
| 2017 | Faster Coordinate Descent via Adaptive Importance Sampling. Dmytro Perekrestenko, Volkan Cevher, Martin Jaggi |
| 2017 | Finite-sum Composition Optimization via Variance Reduced Gradient Descent. Xiangru Lian, Mengdi Wang, Ji Liu |
| 2017 | Frank-Wolfe Algorithms for Saddle Point Problems. Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien |
| 2017 | Frequency Domain Predictive Modelling with Aggregated Data. Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo |
| 2017 | Generalization Error of Invariant Classifiers. Jure Sokolic, Raja Giryes, Guillermo Sapiro, Miguel R. D. Rodrigues |
| 2017 | Generalized Pseudolikelihood Methods for Inverse Covariance Estimation. Alnur Ali, Kshitij Khare, Sang-Yun Oh, Bala Rajaratnam |
| 2017 | Global Convergence of Non-Convex Gradient Descent for Computing Matrix Squareroot. Prateek Jain, Chi Jin, Sham M. Kakade, Praneeth Netrapalli |
| 2017 | Gradient Boosting on Stochastic Data Streams. Hanzhang Hu, Wen Sun, Arun Venkatraman, Martial Hebert, J. Andrew Bagnell |
| 2017 | Gray-box Inference for Structured Gaussian Process Models. Pietro Galliani, Amir Dezfouli, Edwin V. Bonilla, Novi Quadrianto |
| 2017 | Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain. Xiangru Huang, Ian En-Hsu Yen, Ruohan Zhang, Qixing Huang, Pradeep Ravikumar, Inderjit S. Dhillon |
| 2017 | Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann, Andreas Krause |
| 2017 | Hierarchically-partitioned Gaussian Process Approximation. Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim |
| 2017 | High-dimensional Time Series Clustering via Cross-Predictability. Dezhi Hong, Quanquan Gu, Kamin Whitehouse |
| 2017 | Hit-and-Run for Sampling and Planning in Non-Convex Spaces. Yasin Abbasi-Yadkori, Peter L. Bartlett, Victor Gabillon, Alan Malek |
| 2017 | Horde of Bandits using Gaussian Markov Random Fields. Sharan Vaswani, Mark Schmidt, Laks V. S. Lakshmanan |
| 2017 | Identifying Groups of Strongly Correlated Variables through Smoothed Ordered Weighted L Raman Sankaran, Francis R. Bach, Chiranjib Bhattacharyya |
| 2017 | Improved Strongly Adaptive Online Learning using Coin Betting. Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett |
| 2017 | Inference Compilation and Universal Probabilistic Programming. Tuan Anh Le, Atilim Gunes Baydin, Frank D. Wood |
| 2017 | Information Projection and Approximate Inference for Structured Sparse Variables. Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo |
| 2017 | Information-theoretic limits of Bayesian network structure learning. Asish Ghoshal, Jean Honorio |
| 2017 | Initialization and Coordinate Optimization for Multi-way Matching. Da Tang, Tony Jebara |
| 2017 | Label Filters for Large Scale Multilabel Classification. Alexandru Niculescu-Mizil, Ehsan Abbasnejad |
| 2017 | Large-Scale Data-Dependent Kernel Approximation. Catalin Ionescu, Alin-Ionut Popa, Cristian Sminchisescu |
| 2017 | Learning Cost-Effective and Interpretable Treatment Regimes. Himabindu Lakkaraju, Cynthia Rudin |
| 2017 | Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions. Asish Ghoshal, Jean Honorio |
| 2017 | Learning Nash Equilibrium for General-Sum Markov Games from Batch Data. Julien Pérolat, Florian Strub, Bilal Piot, Olivier Pietquin |
| 2017 | Learning Nonparametric Forest Graphical Models with Prior Information. Yuancheng Zhu, Zhe Liu, Siqi Sun |
| 2017 | Learning Optimal Interventions. Jonas Mueller, David Reshef, George Du, Tommi S. Jaakkola |
| 2017 | Learning Structured Weight Uncertainty in Bayesian Neural Networks. Shengyang Sun, Changyou Chen, Lawrence Carin |
| 2017 | Learning Theory for Conditional Risk Minimization. Alexander Zimin, Christoph H. Lampert |
| 2017 | Learning Time Series Detection Models from Temporally Imprecise Labels. Roy J. Adams, Benjamin M. Marlin |
| 2017 | Learning from Conditional Distributions via Dual Embeddings. Bo Dai, Niao He, Yunpeng Pan, Byron Boots, Le Song |
| 2017 | Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields. Youngsuk Park, David Hallac, Stephen P. Boyd, Jure Leskovec |
| 2017 | Learning with Feature Feedback: from Theory to Practice. Stefanos Poulis, Sanjoy Dasgupta |
| 2017 | Least-Squares Log-Density Gradient Clustering for Riemannian Manifolds. Mina Ashizawa, Hiroaki Sasaki, Tomoya Sakai, Masashi Sugiyama |
| 2017 | Less than a Single Pass: Stochastically Controlled Stochastic Gradient. Lihua Lei, Michael I. Jordan |
| 2017 | Linear Convergence of Stochastic Frank Wolfe Variants. Donald Goldfarb, Garud Iyengar, Chaoxu Zhou |
| 2017 | Linear Thompson Sampling Revisited. Marc Abeille, Alessandro Lazaric |
| 2017 | Linking Micro Event History to Macro Prediction in Point Process Models. Yichen Wang, Xiaojing Ye, Haomin Zhou, Hongyuan Zha, Le Song |
| 2017 | Lipschitz Density-Ratios, Structured Data, and Data-driven Tuning. Samory Kpotufe |
| 2017 | Local Group Invariant Representations via Orbit Embeddings. Anant Raj, Abhishek Kumar, Youssef Mroueh, Tom Fletcher, Bernhard Schölkopf |
| 2017 | Local Perturb-and-MAP for Structured Prediction. Gedas Bertasius, Qiang Liu, Lorenzo Torresani, Jianbo Shi |
| 2017 | Localized Lasso for High-Dimensional Regression. Makoto Yamada, Koh Takeuchi, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski |
| 2017 | Lower Bounds on Active Learning for Graphical Model Selection. Jonathan Scarlett, Volkan Cevher |
| 2017 | Markov Chain Truncation for Doubly-Intractable Inference. Colin Wei, Iain Murray |
| 2017 | Minimax Approach to Variable Fidelity Data Interpolation. Alexey Zaytsev, Evgeny Burnaev |
| 2017 | Minimax Density Estimation for Growing Dimension. Daniel McDonald |
| 2017 | Minimax Gaussian Classification & Clustering. Tianyang Li, Xinyang Yi, Constantine Caramanis, Pradeep Ravikumar |
| 2017 | Minimax-optimal semi-supervised regression on unknown manifolds. Amit Moscovich, Ariel Jaffe, Boaz Nadler |
| 2017 | Modal-set estimation with an application to clustering. Heinrich Jiang, Samory Kpotufe |
| 2017 | Near-optimal Bayesian Active Learning with Correlated and Noisy Tests. Yuxin Chen, Seyed Hamed Hassani, Andreas Krause |
| 2017 | Nearly Instance Optimal Sample Complexity Bounds for Top-k Arm Selection. Lijie Chen, Jian Li, Mingda Qiao |
| 2017 | Non-Count Symmetries in Boolean & Multi-Valued Prob. Graphical Models. Ankit Anand, Ritesh Noothigattu, Parag Singla, Mausam |
| 2017 | Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach. Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi |
| 2017 | Nonlinear ICA of Temporally Dependent Stationary Sources. Aapo Hyvärinen, Hiroshi Morioka |
| 2017 | On the Hyperprior Choice for the Global Shrinkage Parameter in the Horseshoe Prior. Juho Piironen, Aki Vehtari |
| 2017 | On the Interpretability of Conditional Probability Estimates in the Agnostic Setting. Yihan Gao, Aditya G. Parameswaran, Jian Peng |
| 2017 | On the Learnability of Fully-Connected Neural Networks. Yuchen Zhang, Jason D. Lee, Martin J. Wainwright, Michael I. Jordan |
| 2017 | On the Troll-Trust Model for Edge Sign Prediction in Social Networks. Géraud Le Falher, Nicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale |
| 2017 | Online Learning and Blackwell Approachability with Partial Monitoring: Optimal Convergence Rates. Joon Kwon, Vianney Perchet |
| 2017 | Online Nonnegative Matrix Factorization with General Divergences. Renbo Zhao, Vincent Yan Fu Tan, Huan Xu |
| 2017 | Online Optimization of Smoothed Piecewise Constant Functions. Vincent Cohen-Addad, Varun Kanade |
| 2017 | Optimal Recovery of Tensor Slices. Vivek F. Farias, Andrew A. Li |
| 2017 | Optimistic Planning for the Stochastic Knapsack Problem. Ciara Pike-Burke, Steffen Grünewälder |
| 2017 | Performance Bounds for Graphical Record Linkage. Rebecca C. Steorts, Matt Barnes, Willie Neiswanger |
| 2017 | Phase Retrieval Meets Statistical Learning Theory: A Flexible Convex Relaxation. Sohail Bahmani, Justin Romberg |
| 2017 | Poisson intensity estimation with reproducing kernels. Seth R. Flaxman, Yee Whye Teh, Dino Sejdinovic |
| 2017 | Prediction Performance After Learning in Gaussian Process Regression. Johan Wågberg, Dave Zachariah, Thomas B. Schön, Petre Stoica |
| 2017 | Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA Aarti Singh, Xiaojin (Jerry) Zhu |
| 2017 | Quantifying the accuracy of approximate diffusions and Markov chains. Jonathan Huggins, James Zou |
| 2017 | Random Consensus Robust PCA. Daniel L. Pimentel-Alarcón, Robert D. Nowak |
| 2017 | Random projection design for scalable implicit smoothing of randomly observed stochastic processes. Francois Belletti, Evan Randall Sparks, Alexandre M. Bayen, Joseph Gonzalez |
| 2017 | Rank Aggregation and Prediction with Item Features. Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon |
| 2017 | Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models. Sejun Park, Yunhun Jang, Andreas Galanis, Jinwoo Shin, Daniel Stefankovic, Eric Vigoda |
| 2017 | Regression Uncertainty on the Grassmannian. Yi Hong, Xiao Yang, Roland Kwitt, Martin Styner, Marc Niethammer |
| 2017 | Regret Bounds for Lifelong Learning. Pierre Alquier, The Tien Mai, Massimiliano Pontil |
| 2017 | Regret Bounds for Transfer Learning in Bayesian Optimisation. Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2017 | Relativistic Monte Carlo. Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever, Yee Whye Teh, Sebastian J. Vollmer |
| 2017 | Removing Phase Transitions from Gibbs Measures. Ian Fellows, Mark Handcock |
| 2017 | Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms. Christian A. Naesseth, Francisco J. R. Ruiz, Scott W. Linderman, David M. Blei |
| 2017 | Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness. Ioan Gabriel Bucur, Tom Claassen, Tom Heskes |
| 2017 | Robust and Efficient Computation of Eigenvectors in a Generalized Spectral Method for Constrained Clustering. Chengming Jiang, Huiqing Xie, Zhaojun Bai |
| 2017 | Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition. Jiong Zhang, Ian En-Hsu Yen, Pradeep Ravikumar, Inderjit S. Dhillon |
| 2017 | Scalable Greedy Feature Selection via Weak Submodularity. Rajiv Khanna, Ethan R. Elenberg, Alexandros G. Dimakis, Sahand N. Negahban, Joydeep Ghosh |
| 2017 | Scalable Learning of Non-Decomposable Objectives. Elad Eban, Mariano Schain, Alan Mackey, Ariel Gordon, Ryan Rifkin, Gal Elidan |
| 2017 | Scalable Variational Inference for Super Resolution Microscopy. Ruoxi Sun, Evan Archer, Liam Paninski |
| 2017 | Scaling Submodular Maximization via Pruned Submodularity Graphs. Tianyi Zhou, Hua Ouyang, Jeff A. Bilmes, Yi Chang, Carlos Guestrin |
| 2017 | Sequential Graph Matching with Sequential Monte Carlo. Seong-Hwan Jun, Samuel W. K. Wong, James V. Zidek, Alexandre Bouchard-Côté |
| 2017 | Sequential Multiple Hypothesis Testing with Type I Error Control. Alan Malek, Sumeet Katariya, Yinlam Chow, Mohammad Ghavamzadeh |
| 2017 | Signal-based Bayesian Seismic Monitoring. David A. Moore, Stuart Russell |
| 2017 | Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data. Jialei Wang, Jason D. Lee, Mehrdad Mahdavi, Mladen Kolar, Nati Srebro |
| 2017 | Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage. Alp Yurtsever, Madeleine Udell, Joel A. Tropp, Volkan Cevher |
| 2017 | Sparse Accelerated Exponential Weights. Pierre Gaillard, Olivier Wintenberger |
| 2017 | Sparse Randomized Partition Trees for Nearest Neighbor Search. Kaushik Sinha, Omid Keivani |
| 2017 | Spatial Decompositions for Large Scale SVMs. Philipp Thomann, Ingrid Blaschzyk, Mona Meister, Ingo Steinwart |
| 2017 | Spectral Methods for Correlated Topic Models. Forough Arabshahi, Anima Anandkumar |
| 2017 | Stochastic Difference of Convex Algorithm and its Application to Training Deep Boltzmann Machines. Atsushi Nitanda, Taiji Suzuki |
| 2017 | Stochastic Rank-1 Bandits. Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Claire Vernade, Zheng Wen |
| 2017 | Structured adaptive and random spinners for fast machine learning computations. Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Francois Fagan, Cédric Gouy-Pailler, Anne Morvan, Nourhan Sakr, Tamás Sarlós, Jamal Atif |
| 2017 | Tensor Decompositions via Two-Mode Higher-Order SVD (HOSVD). Miaoyan Wang, Yun S. Song |
| 2017 | Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis. Andrew Stevens, Yunchen Pu, Yannan Sun, Gregory Spell, Lawrence Carin |
| 2017 | The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits. Tor Lattimore, Csaba Szepesvári |
| 2017 | Thompson Sampling for Linear-Quadratic Control Problems. Marc Abeille, Alessandro Lazaric |
| 2017 | Tracking Objects with Higher Order Interactions via Delayed Column Generation. Shaofei Wang, Steffen Wolf, Charless C. Fowlkes, Julian Yarkony |
| 2017 | Trading off Rewards and Errors in Multi-Armed Bandits. Akram Erraqabi, Alessandro Lazaric, Michal Valko, Emma Brunskill, Yun-En Liu |
| 2017 | Unsupervised Sequential Sensor Acquisition. Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama |
| 2017 | Value-Aware Loss Function for Model-based Reinforcement Learning. Amir Massoud Farahmand, André Barreto, Daniel Nikovski |