Papers
Sampling from Non-Log-Concave Distributions via Variance-Reduced Gradient Langevin Dynamics
Difan Zou, Pan Xu, Quanquan Gu
Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective
Anirudh Vemula, Wen Sun, J. Bagnell
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
Dhruv Malik, Ashwin Pananjady, Kush Bhatia et al.
Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models
Craig Kelly, Somdeb Sarkhel, Deepak Venugopal
Decentralized Gradient Tracking for Continuous DR-Submodular Maximization
Jiahao Xie, Chao Zhang, Zebang Shen et al.
Efficient Greedy Coordinate Descent for Composite Problems
Sai Praneeth Karimireddy, Anastasia Koloskova, Sebastian U. Stich et al.
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference
Mike Wu, Noah Goodman, Stefano Ermon
Complexities in Projection-Free Stochastic Non-convex Minimization
Zebang Shen, Cong Fang, Peilin Zhao et al.
On the Dynamics of Gradient Descent for Autoencoders
Thanh V. Nguyen, Raymond K. W. Wong, Chinmay Hegde
Deep Topic Models for Multi-label Learning
Rajat Panda, Ankit Pensia, Nikhil Mehta et al.
On Theory for BART
Veronika Ročková, Enakshi Saha
AutoML from Service Provider’s Perspective: Multi-device, Multi-tenant Model Selection with GP-EI
Chen Yu, Bojan Karlaš, Jie Zhong et al.
Exploring k out of Top ρ Fraction of Arms in Stochastic Bandits
Wenbo Ren, Jia Liu, Ness B. Shroff
Precision Matrix Estimation with Noisy and Missing Data
Roger Fan, Byoungwook Jang, Yuekai Sun et al.
Region-Based Active Learning
Corinna Cortes, Giulia DeSalvo, Claudio Gentile et al.
A Unified Weight Learning Paradigm for Multi-view Learning
Lai Tian, Feiping Nie, Xuelong Li
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era
Nicolas Durrande, Vincent Adam, Lucas Bordeaux et al.
Cost aware Inference for IoT Devices
Pengkai Zhu, Durmus Alp Emre Acar, Nan Feng et al.
High Dimensional Inference in Partially Linear Models
Ying Zhu, Zhuqing Yu, Guang Cheng
Improving Quadrature for Constrained Integrands
Henry R. Chai, Roman Garnett
Variational Noise-Contrastive Estimation
Benjamin Rhodes, Michael U. Gutmann
Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization
Zhe Wang, Yi Zhou, Yingbin Liang et al.
Hierarchical Clustering for Euclidean Data
Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh et al.
Variance reduction properties of the reparameterization trick
Ming Xu, Matias Quiroz, Robert Kohn et al.
Adaptive MCMC via Combining Local Samplers
Kiárash Shaloudegi, András György