NIPS Proceedings
β
Books
Manfred K. K. Warmuth
22 Papers
Robust Bi-Tempered Logistic Loss Based on Bregman Divergences
(2019)
Leveraged volume sampling for linear regression
(2018)
Online Dynamic Programming
(2017)
Unbiased estimates for linear regression via volume sampling
(2017)
The limits of squared Euclidean distance regularization
(2014)
Putting Bayes to sleep
(2012)
Learning Eigenvectors for Free
(2011)
Repeated Games against Budgeted Adversaries
(2010)
Boosting Algorithms for Maximizing the Soft Margin
(2007)
Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension
(2006)
A Bayes Rule for Density Matrices
(2005)
Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection
(2004)
Boosting versus Covering
(2003)
Adaptive Caching by Refetching
(2002)
Active Learning in the Drug Discovery Process
(2001)
On the Convergence of Leveraging
(2001)
Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy
(1998)
Linear Hinge Loss and Average Margin
(1998)
Relative Loss Bounds for Multidimensional Regression Problems
(1997)
Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions
(1996)
Exponentially many local minima for single neurons
(1995)
Worst-case Loss Bounds for Single Neurons
(1995)