Papers
8,340 papers found
An Asynchronous Distributed Proximal Gradient Method for Composite Convex Optimization
Necdet Aybat, Zi Wang, Garud Iyengar
A Nearly-Linear Time Framework for Graph-Structured Sparsity
Chinmay Hegde, Piotr Indyk, Ludwig Schmidt
An embarrassingly simple approach to zero-shot learning
Bernardino Romera-Paredes, Philip Torr
An Empirical Exploration of Recurrent Network Architectures
Rafal Jozefowicz, Wojciech Zaremba, Ilya Sutskever
An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process
Amar Shah, David Knowles, Zoubin Ghahramani
A New Generalized Error Path Algorithm for Model Selection
Bin Gu, Charles Ling
An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection
Tianbao Yang, Lijun Zhang, Rong Jin et al.
An Online Learning Algorithm for Bilinear Models
Yuanbin Wu, Shiliang Sun
Approval Voting and Incentives in Crowdsourcing
Nihar Shah, Dengyong Zhou, Yuval Peres
Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games
Julien Perolat, Bruno Scherrer, Bilal Piot et al.
A Probabilistic Model for Dirty Multi-task Feature Selection
Daniel Hernandez-Lobato, Jose Miguel Hernandez-Lobato, Zoubin Ghahramani
A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning
Debarghya Ghoshdastidar, Ambedkar Dukkipati
A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling Bandits
Pratik Gajane, Tanguy Urvoy, Fabrice Clérot
Asymmetric Transfer Learning with Deep Gaussian Processes
Melih Kandemir
A Theoretical Analysis of Metric Hypothesis Transfer Learning
Michaël Perrot, Amaury Habrard
Atomic Spatial Processes
Sean Jewell, Neil Spencer, Alexandre Bouchard-Côté
A trust-region method for stochastic variational inference with applications to streaming data
Lucas Theis, Matt Hoffman
Attribute Efficient Linear Regression with Distribution-Dependent Sampling
Doron Kukliansky, Ohad Shamir
A Unified Framework for Outlier-Robust PCA-like Algorithms
Wenzhuo Yang, Huan Xu
A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data
Trong Nghia Hoang, Quang Minh Hoang, Bryan Kian Hsiang Low
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe, Christian Szegedy
Bayesian and Empirical Bayesian Forests
Taddy Matthew, Chun-Sheng Chen, Jun Yu et al.
Bayesian Multiple Target Localization
Purnima Rajan, Weidong Han, Raphael Sznitman et al.
BilBOWA: Fast Bilingual Distributed Representations without Word Alignments
Stephan Gouws, Yoshua Bengio, Greg Corrado