1.4k citations · 4.5k across the 58 of their papers we have counts for
4 papers · 2 filters
Flexible Modeling of Latent Task Structures in Multitask Learning
Alexandre Passos, Piyush Rai, Jacques Wainer +1
Multitask learning algorithms are typically designed assuming some fixed, a priori known latent structure shared by all the tasks. However, it is usually unclear what type of laten…
A Binary Classification Framework for Two-Stage Multiple Kernel Learning
Abhishek Kumar, Alexandru Niculescu-Mizil, Koray Kavukcuoglu +1
With the advent of kernel methods, automating the task of specifying a suitable kernel has become increasingly important. In this context, the Multiple Kernel Learning (MKL) proble…
Learning Task Grouping and Overlap in Multi-task Learning
Abhishek Kumar, Hal Daume
In the paradigm of multi-task learning, mul- tiple related prediction tasks are learned jointly, sharing information across the tasks. We propose a framework for multi-task learn-…
Efficient Protocols for Distributed Classification and Optimization
Hal Daume, Jeff M. Phillips, Avishek Saha +1
In distributed learning, the goal is to perform a learning task over data distributed across multiple nodes with minimal (expensive) communication. Prior work (Daume III et al., 20…