Papers
Adaptive Bayesian Sampling with Monte Carlo EM
Anirban Roychowdhury, Srinivasan Parthasarathy
Adaptive Classification for Prediction Under a Budget
Feng Nan, Venkatesh Saligrama
Adaptive Clustering through Semidefinite Programming
Martin Royer
Adaptive stimulus selection for optimizing neural population responses
Benjamin Cowley, Ryan Williamson, Katerina Clemens et al.
Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth Parameter
Yi Xu, Qihang Lin, Tianbao Yang
A Decomposition of Forecast Error in Prediction Markets
Miro Dudik, Sebastien Lahaie, Ryan M Rogers et al.
A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering
Hongteng Xu, Hongyuan Zha
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning
Marco Fraccaro, Simon Kamronn, Ulrich Paquet et al.
ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization
Yi Xu, Mingrui Liu, Qihang Lin et al.
Adversarial Ranking for Language Generation
Kevin Lin, Dianqi Li, Xiaodong He et al.
Adversarial Surrogate Losses for Ordinal Regression
Rizal Fathony, Mohammad Ali Bashiri, Brian Ziebart
Adversarial Symmetric Variational Autoencoder
Yuchen Pu, Weiyao Wang, Ricardo Henao et al.
Affine-Invariant Online Optimization and the Low-rank Experts Problem
Tomer Koren, Roi Livni
Affinity Clustering: Hierarchical Clustering at Scale
Mohammadhossein Bateni, Soheil Behnezhad, Mahsa Derakhshan et al.
A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control
Fanny Yang, Aaditya Ramdas, Kevin G. Jamieson et al.
A General Framework for Robust Interactive Learning
Ehsan Emamjomeh-Zadeh, David Kempe
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification
Bikash Joshi, Massih R. Amini, Ioannis Partalas et al.
A graph-theoretic approach to multitasking
Noga Alon, Daniel Reichman, Igor Shinkar et al.
A Greedy Approach for Budgeted Maximum Inner Product Search
Hsiang-Fu Yu, Cho-Jui Hsieh, Qi Lei et al.
AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms
Marco Cusumano-Towner, Vikash K Mansinghka
A KL-LUCB algorithm for Large-Scale Crowdsourcing
Ervin Tanczos, Robert Nowak, Bob Mankoff
A Learning Error Analysis for Structured Prediction with Approximate Inference
Yuanbin Wu, Man Lan, Shiliang Sun et al.
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching
Chunyuan Li, Hao Liu, Changyou Chen et al.
A Linear-Time Kernel Goodness-of-Fit Test
Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo et al.
Alternating Estimation for Structured High-Dimensional Multi-Response Models
Sheng Chen, Arindam Banerjee