Papers
Best of many worlds: Robust model selection for online supervised learning
Vidya Muthukumar, Mitas Ray, Anant Sahai et al.
Online Algorithm for Unsupervised Sensor Selection
Arun Verma, Manjesh Hanawal, Csaba Szepesvari et al.
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes
Jialin Song, Yuxin Chen, Yisong Yue
Probabilistic Multilevel Clustering via Composite Transportation Distance
Nhat Ho, Viet Huynh, Dinh Phung et al.
Sample-Efficient Imitation Learning via Generative Adversarial Nets
Lionel Blondé, Alexandros Kalousis
Structured Robust Submodular Maximization: Offline and Online Algorithms
Nima Anari, Nika Haghtalab, Seffi Naor et al.
Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport
Adarsh Subbaswamy, Peter Schulam, Suchi Saria
Model-Free Linear Quadratic Control via Reduction to Expert Prediction
Yasin Abbasi-Yadkori, Nevena Lazic, Csaba Szepesvari
Adaptive Estimation for Approximate k-Nearest-Neighbor Computations
Daniel LeJeune, Reinhard Heckel, Richard Baraniuk
Adversarial Discrete Sequence Generation without Explicit NeuralNetworks as Discriminators
Zhongliang Li, Tian Xia, Xingyu Lou et al.
A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects
Daniel Malinsky, Ilya Shpitser, Thomas Richardson
A recurrent Markov state-space generative model for sequences
Anand Ramachandran, Steve Lumetta, Eric Klee et al.
Deep Switch Networks for Generating Discrete Data and Language
Payam Delgosha, Naveen Goela
Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate
Mor Shpigel Nacson, Nathan Srebro, Daniel Soudry
Optimizing over a Restricted Policy Class in MDPs
Ershad Banijamali, Yasin Abbasi-Yadkori, Mohammad Ghavamzadeh et al.
Improved Semi-Supervised Learning with Multiple Graphs
Krishnamurthy Viswanathan, Sushant Sachdeva, Andrew Tomkins et al.
Binary Space Partitioning Forest
Xuhui Fan, Bin Li, Scott SIsson
Minimum Volume Topic Modeling
Byoungwook Jang, Alfred Hero
A Fast Sampling Algorithm for Maximum Inner Product Search
QIN DING, Hsiang-Fu Yu, Cho-Jui Hsieh
Theoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning
Tadashi Kozuno, Eiji Uchibe, Kenji Doya
Learning the Structure of a Nonstationary Vector Autoregression
Daniel Malinsky, Peter Spirtes
Sobolev Descent
Youssef Mroueh, Tom Sercu, Anant Raj
A maximum-mean-discrepancy goodness-of-fit test for censored data
Tamara Fernandez, Arthur Gretton
Imitation-Regularized Offline Learning
Yifei Ma, Yu-Xiang Wang, Balakrishnan Narayanaswamy
Graph to Graph: a Topology Aware Approach for Graph Structures Learning and Generation
Mingming Sun, Ping Li