Papers
Communication-efficient Distributed Sparse Linear Discriminant Analysis
Lu Tian, Quanquan Gu
A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models
Beilun Wang, Ji Gao, Yanjun Qi
Finite-sum Composition Optimization via Variance Reduced Gradient Descent
Xiangru Lian, Mengdi Wang, Ji Liu
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data
Jialei Wang, Jason Lee, Mehrdad Mahdavi et al.
Belief Propagation in Conditional RBMs for Structured Prediction
Wei Ping, Alex Ihler
Tracking Objects with Higher Order Interactions via Delayed Column Generation
Shaofei Wang, Steffen Wolf, Charless Fowlkes et al.
Identifying Groups of Strongly Correlated Variables through Smoothed Ordered Weighted L_1-norms
Raman Sankaran, Francis Bach, Chiranjib Bhattacharya
Optimistic Planning for the Stochastic Knapsack Problem
Ciara Pike-Burke, Steffen Grunewalder
Learning with Feature Feedback: from Theory to Practice
Stefanos Poulis, Sanjoy Dasgupta
Generalization Error of Invariant Classifiers
Jure Sokolic, Raja Giryes, Guillermo Sapiro et al.
Sequential Graph Matching with Sequential Monte Carlo
Seong-Hwan Jun, Samuel W.K. Wong, James Zidek et al.
Linear Convergence of Stochastic Frank Wolfe Variants
Donald Goldfarb, Garud Iyengar, Chaoxu Zhou
Scalable Variational Inference for Super Resolution Microscopy
Ruoxi Sun, Evan Archer, Liam Paninski
Learning Optimal Interventions
Jonas Mueller, David Reshef, George Du et al.
Complementary Sum Sampling for Likelihood Approximation in Large Scale Classification
Aleksandar Botev, Bowen Zheng, David Barber
Structured adaptive and random spinners for fast machine learning computations
Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski et al.
Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere
Albert Thomas, Stéphan Clemencon, Alexandre Gramfort et al.
A Learning Theory of Ranking Aggregation
Anna Korba, Stéphan Clemencon, Eric Sibony
A New Class of Private Chi-Square Hypothesis Tests
Ryan Rogers, Daniel Kifer
A Unified Computational and Statistical Framework for Nonconvex Low-rank Matrix Estimation
Lingxiao Wang, Xiao Zhang, Quanquan Gu
Frequency Domain Predictive Modelling with Aggregated Data
Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo
Fairness Constraints: Mechanisms for Fair Classification
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rogriguez et al.
Black-box Importance Sampling
Qiang Liu, Jason Lee