Papers
4,025 papers found
A recurrent Markov state-space generative model for sequences
Anand Ramachandran, Steve Lumetta, Eric Klee et al.
Are we there yet? Manifold identification of gradient-related proximal methods
Yifan Sun, Halyun Jeong, Julie Nutini et al.
A Robust Zero-Sum Game Framework for Pool-based Active Learning
Dixian Zhu, Zhe Li, Xiaoyu Wang et al.
A Stein–Papangelou Goodness-of-Fit Test for Point Processes
Jiasen Yang, Vinayak Rao, Jennifer Neville
A Swiss Army Infinitesimal Jackknife
Ryan Giordano, William Stephenson, Runjing Liu et al.
A Thompson Sampling Algorithm for Cascading Bandits
Wang Chi Cheung, Vincent Tan, Zixin Zhong
A Topological Regularizer for Classifiers via Persistent Homology
Chao Chen, Xiuyan Ni, Qinxun Bai et al.
Attenuating Bias in Word vectors
Sunipa Dev, Jeff Phillips
Augmented Ensemble MCMC sampling in Factorial Hidden Markov Models
Kaspar Märtens, Michalis Titsias, Christopher Yau
A Unified Weight Learning Paradigm for Multi-view Learning
Lai Tian, Feiping Nie, Xuelong Li
Autoencoding any Data through Kernel Autoencoders
Pierre Laforgue, Stéphan Clémençon, Florence d’Alche-Buc
Auto-Encoding Total Correlation Explanation
Shuyang Gao, Rob Brekelmans, Greg Ver Steeg et al.
AutoML from Service Provider’s Perspective: Multi-device, Multi-tenant Model Selection with GP-EI
Chen Yu, Bojan Karlaš, Jie Zhong et al.
Avoiding Latent Variable Collapse with Generative Skip Models
Adji B. Dieng, Yoon Kim, Alexander M. Rush et al.
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era
Nicolas Durrande, Vincent Adam, Lucas Bordeaux et al.
Bandit Online Learning with Unknown Delays
Bingcong Li, Tianyi Chen, Georgios B. Giannakis
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design
Kevin K. Yang, Yuxin Chen, Alycia Lee et al.
Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference
Kelvin Hsu, Fabio Ramos
Bayesian Learning of Neural Network Architectures
Georgi Dikov, Justin Bayer
Bayesian optimisation under uncertain inputs
Rafael Oliveira, Lionel Ott, Fabio Ramos
Bernoulli Race Particle Filters
Sebastian M. Schmon, Arnaud Doucet, George Deligiannidis
Best of many worlds: Robust model selection for online supervised learning
Vidya Muthukumar, Mitas Ray, Anant Sahai et al.
Binary Space Partitioning Forest
Xuhui Fan, Bin Li, Scott SIsson
Black Box Quantiles for Kernel Learning
Anthony Tompkins, Ransalu Senanayake, Philippe Morere et al.
Blind Demixing via Wirtinger Flow with Random Initialization
Jialin Dong, Yuanming Shi