Papers
Derivative Free Optimization Via Repeated Classification
Tatsunori Hashimoto, Steve Yadlowsky, John Duchi
Probability–Revealing Samples
Krzysztof Onak, Xiaorui Sun
HONES: A Fast and Tuning-free Homotopy Method For Online Newton Step
Yuting Ye, Lihua Lei, Cheng Ju
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning
Dong Yin, Ashwin Pananjady, Max Lam et al.
Labeled Graph Clustering via Projected Gradient Descent
Shiau Hong Lim, Gregory Calvez
Learning Hidden Quantum Markov Models
Siddarth Srinivasan, Geoff Gordon, Byron Boots
Near-Optimal Machine Teaching via Explanatory Teaching Sets
Yuxin Chen, Oisin Mac Aodha, Shihan Su et al.
Proximity Variational Inference
Jaan Altosaar, Rajesh Ranganath, David Blei
Nonparametric Bayesian sparse graph linear dynamical systems
Rahi Kalantari, Joydeep Ghosh, Mingyuan Zhou
Bayesian Multi-label Learning with Sparse Features and Labels, and Label Co-occurrences
He Zhao, Piyush Rai, Lan Du et al.
Spectral Algorithms for Computing Fair Support Vector Machines
Mahbod Olfat, Anil Aswani
The emergence of spectral universality in deep networks
Jeffrey Pennington, Samuel Schoenholz, Surya Ganguli
Matrix-normal models for fMRI analysis
Michael Shvartsman, Narayanan Sundaram, Mikio Aoi et al.
Efficient Bayesian Methods for Counting Processes in Partially Observable Environments
Ferdian Jovan, Jeremy Wyatt, Nick Hawes
Online Continuous Submodular Maximization
Lin Chen, Hamed Hassani, Amin Karbasi
Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap
Aryan Mokhtari, Hamed Hassani, Amin Karbasi
Scalable Hash-Based Estimation of Divergence Measures
Morteza Noshad, Alfred Hero
On denoising modulo 1 samples of a function
Mihai Cucuringu, Hemant Tyagi
The Binary Space Partitioning-Tree Process
Xuhui Fan, Bin Li, Scott Sisson
Comparison Based Learning from Weak Oracles
Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta et al.
Adaptive Sampling for Coarse Ranking
Sumeet Katariya, Lalit Jain, Nandana Sengupta et al.
The Power Mean Laplacian for Multilayer Graph Clustering
Pedro Mercado, Antoine Gautier, Francesco Tudisco et al.
Parallel and Distributed MCMC via Shepherding Distributions
Arkabandhu Chowdhury, Christopher Jermaine
Inference in Sparse Graphs with Pairwise Measurements and Side Information
Dylan Foster, Karthik Sridharan, Daniel Reichman
Convergence of Value Aggregation for Imitation Learning
Ching-An Cheng, Byron Boots