989 citations · 6.1k across the 184 of their papers we have counts for
4 papers · 2 filters
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Niranjan Srinivas, Andreas Krause, Sham M. Kakade +1
Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multi-armed bandit problem, where the payoff function is…
Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity
Sham M. Kakade, Ohad Shamir, Karthik Sridharan +1
The versatility of exponential families, along with their attendant convexity properties, make them a popular and effective statistical model. A central issue is learning these mod…
Regularization Techniques for Learning with Matrices
Sham M. Kakade, Shai Shalev-Shwartz, Ambuj Tewari
There is growing body of learning problems for which it is natural to organize the parameters into matrix, so as to appropriately regularize the parameters under some matrix norm (…
Multi-Label Prediction via Compressed Sensing
Daniel Hsu, Sham M. Kakade, John Langford +1
We consider multi-label prediction problems with large output spaces under the assumption of output sparsity -- that the target (label) vectors have small support. We develop a gen…