Provable Accelerated Bayesian Optimization with Knowledge Transfer
haitao-lin
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1 min read
High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching
This paper addresses differential inference in time-varying parametric probabilistic models, like graphical models with changing structures. Instead of estimating a …
daniel-j.-williams
Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
dake-zhang
On the Lasso for Graphical Continuous Lyapunov Models
Graphical continuous Lyapunov models offer a new perspective on modeling causally interpretable dependence structure in multivariate data by treating each independent observation …
philipp-dettling
Inconsistency of cross-validation for structure learning in Gaussian graphical models
Despite numerous years of research into the merits and trade-offs of various model selection criteria, obtaining robust results that elucidate the behavior of cross-validation …
zhao-lyu
One Policy is Enough: Parallel Exploration with a Single Policy is Minimax Optimal for Reward-Free Reinforcement Learning
Although parallelism has been extensively used in Reinforcement Learning (RL), the quantitative effects of parallel exploration are not well understood theoretically. We study the …
Differentially Private Matrix Completion through Low-rank Matrix Factorization
We study the matrix completion problem under joint differential privacy and develop a non-convex low-rank matrix factorization-based method for solving it. Our method comes with …
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching
We consider solving equality-constrained nonlinear, nonconvex optimization problems. This class of problems appears widely in a variety of applications in machine learning and …
