Papers
8,340 papers found
Correlation Clustering in Data Streams
KookJin Ahn, Graham Cormode, Sudipto Guha et al.
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback
Adith Swaminathan, Thorsten Joachims
CUR Algorithm for Partially Observed Matrices
Miao Xu, Rong Jin, Zhi-Hua Zhou
Dealing with small data: On the generalization of context trees
Ralf Eggeling, Mikko Koivisto, Ivo Grosse
Deep Edge-Aware Filters
Li Xu, Jimmy Ren, Qiong Yan et al.
Deep Learning with Limited Numerical Precision
Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan et al.
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan et al.
Deterministic Independent Component Analysis
Ruitong Huang, Andras Gyorgy, Csaba Szepesvári
Differentially Private Bayesian Optimization
Matt Kusner, Jacob Gardner, Roman Garnett et al.
DiSCO: Distributed Optimization for Self-Concordant Empirical Loss
Yuchen Zhang, Xiao Lin
Discovering Temporal Causal Relations from Subsampled Data
Mingming Gong, Kun Zhang, Bernhard Schoelkopf et al.
Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM
Ching-Pei Lee, Dan Roth
Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower Bounds
Yuchen Zhang, Martin Wainwright, Michael Jordan
Distributed Gaussian Processes
Marc Deisenroth, Jun Wei Ng
Distributed Inference for Dirichlet Process Mixture Models
Hong Ge, Yutian Chen, Moquan Wan et al.
Distributional Rank Aggregation, and an Axiomatic Analysis
Adarsh Prasad, Harsh Pareek, Pradeep Ravikumar
Double Nyström Method: An Efficient and Accurate Nyström Scheme for Large-Scale Data Sets
Woosang Lim, Minhwan Kim, Haesun Park et al.
DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics
Yining Wang, Jun Zhu
DRAW: A Recurrent Neural Network For Image Generation
Karol Gregor, Ivo Danihelka, Alex Graves et al.
Dynamic Sensing: Better Classification under Acquisition Constraints
Oran Richman, Shie Mannor
Efficient Learning in Large-Scale Combinatorial Semi-Bandits
Zheng Wen, Branislav Kveton, Azin Ashkan
Efficient Training of LDA on a GPU by Mean-for-Mode Estimation
Jean-Baptiste Tristan, Joseph Tassarotti, Guy Steele
\ell_1,p-Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order Methods
Zirui Zhou, Qi Zhang, Anthony Man-Cho So
Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE)
Maurizio Filippone, Raphael Engler
Entropic Graph-based Posterior Regularization
Maxwell Libbrecht, Michael Hoffman, Jeff Bilmes et al.