109
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
117
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
Recent research in machine learning has focused on breaking audio spectrograms into separate sources of sound using latent variable decompositions. These methods require that the ...
76
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
Maximum a posteriori (MAP) inference in graphical models requires that we maximize the sum of two terms: a data-dependent term, encoding the conditional likelihood of a certain la...
103
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
We consider the problem of how to improve the efficiency of Multiple Kernel Learning (MKL). In literature, MKL is often solved by an alternating approach: (1) the minimization of ...
72
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
132
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
Many temporal processes can be naturally modeled as a stochastic system that evolves continuously over time. The representation language of continuous-time Bayesian networks allow...
70
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
101
click to vote
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
We propose a novel dependent hierarchical Pitman-Yor process model for discrete data. An incremental Monte Carlo inference procedure for this model is developed. We show that infe...
99
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) in the off-policy learning context and with the simulation-based least square...
70
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
