Papers
4,025 papers found
Finite-sum Composition Optimization via Variance Reduced Gradient Descent
Xiangru Lian, Mengdi Wang, Ji Liu
Frank-Wolfe Algorithms for Saddle Point Problems
Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien
Frequency Domain Predictive Modelling with Aggregated Data
Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo
Generalization Error of Invariant Classifiers
Jure Sokolic, Raja Giryes, Guillermo Sapiro et al.
Generalized Pseudolikelihood Methods for Inverse Covariance Estimation
Alnur Ali, Kshitij Khare, Sang-Yun Oh et al.
Global Convergence of Non-Convex Gradient Descent for Computing Matrix Squareroot
Prateek Jain, Chi Jin, Sham Kakade et al.
Gradient Boosting on Stochastic Data Streams
Hanzhang Hu, Wen Sun, Arun Venkatraman et al.
Gray-box Inference for Structured Gaussian Process Models
Pietro Galliani, Amir Dezfouli, Edwin Bonilla et al.
Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain
Xiangru Huang, Ian En-Hsu Yen, Ruohan Zhang et al.
Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains
Andrew An Bian, Baharan Mirzasoleiman, Joachim Buhmann et al.
Hierarchically-partitioned Gaussian Process Approximation
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
High-dimensional Time Series Clustering via Cross-Predictability
Dezhi Hong, Quanquan Gu, Kamin Whitehouse
Hit-and-Run for Sampling and Planning in Non-Convex Spaces
Yasin Abbasi-Yadkori, Peter Bartlett, Victor Gabillon et al.
Horde of Bandits using Gaussian Markov Random Fields
Sharan Vaswani, Mark Schmidt, Laks Lakshmanan
Identifying Groups of Strongly Correlated Variables through Smoothed Ordered Weighted $L_1$-norms
Raman Sankaran, Francis Bach, Chiranjib Bhattacharya
Improved Strongly Adaptive Online Learning using Coin Betting
Kwang-Sung Jun, Francesco Orabona, Stephen Wright et al.
Inference Compilation and Universal Probabilistic Programming
Tuan Anh Le, Atilim Gunes Baydin, Frank Wood
Information Projection and Approximate Inference for Structured Sparse Variables
Rajiv Khanna, Joydeep Ghosh, Rusell Poldrack et al.
Information-theoretic limits of Bayesian network structure learning
Asish Ghoshal, Jean Honorio
Initialization and Coordinate Optimization for Multi-way Matching
Da Tang, Tony Jebara
Label Filters for Large Scale Multilabel Classification
Alexandru Niculescu-Mizil, Ehsan Abbasnejad
Large-Scale Data-Dependent Kernel Approximation
Catalin Ionescu, Alin Popa, Cristian Sminchisescu
Learning Cost-Effective and Interpretable Treatment Regimes
Himabindu Lakkaraju, Cynthia Rudin
Learning from Conditional Distributions via Dual Embeddings
Bo Dai, Niao He, Yunpeng Pan et al.
Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions
Asish Ghoshal, Jean Honorio