Education
Online-Within-Online Meta-Learning
Giulia Denevi, Dimitris Stamos, Carlo Ciliberto, Massimiliano Pontil
Neural Information Processing Systems http://nips.cc/
Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD
PHUONG_HA NGUYEN, Lam Nguyen, Marten van Dijk
Neural Information Processing Systems http://nips.cc/
Amortized Bethe Free Energy Minimization for Learning MRFs
We propose to learn deep undirected graphical models (i.e., MRFs) with a non-ELBO objective for which we can calculate exact gradients.
A Universally Optimal Multistage Accelerated Stochastic Gradient Method
Necdet Serhat Aybat, Alireza Fallah, Mert Gurbuzbalaban, Asuman Ozdaglar
Neural Information Processing Systems http://nips.cc/
Thinning for Accelerating the Learning of Point Processes
Neural Information Processing Systems http://nips.cc/
Unsupervised Curricula for Visual Meta-Reinforcement Learning
Allan Jabri, Kyle Hsu, Abhishek Gupta, Ben Eysenbach, Sergey Levine, Chelsea Finn
Neural Information Processing Systems http://nips.cc/
Bandits with Feedback Graphs and Switching Costs
Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri
We give two new algorithms for this problem in the informed setting.
Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration
Kwang-Sung Jun, Ashok Cutkosky, Francesco Orabona
In this paper, we consider the nonparametric least square regression in a Reproducing Kernel Hilbert Space (RKHS).