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ICML
2010
IEEE
14 years 19 days ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
ICML
2010
IEEE
14 years 19 days ago
Probabilistic Backward and Forward Reasoning in Stochastic Relational Worlds
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
Tobias Lang, Marc Toussaint
ICML
2010
IEEE
14 years 19 days ago
3D Convolutional Neural Networks for Human Action Recognition
We consider the fully automated recognition of actions in uncontrolled environment. Most existing work relies on domain knowledge to construct complex handcrafted features from in...
Shuiwang Ji, Wei Xu, Ming Yang, Kai Yu
ICML
2010
IEEE
14 years 19 days ago
Modeling Transfer Learning in Human Categorization with the Hierarchical Dirichlet Process
Transfer learning can be described as the tion of abstract knowledge from one learning domain or task and the reuse of that knowledge in a related domain or task. In categorizatio...
Kevin R. Canini, Mikhail M. Shashkov, Thomas L. Gr...
ICML
2010
IEEE
14 years 19 days ago
SVM Classifier Estimation from Group Probabilities
A learning problem that has only recently gained attention in the machine learning community is that of learning a classifier from group probabilities. It is a learning task that ...
Stefan Rüping
ICML
2010
IEEE
14 years 19 days ago
Fast Neighborhood Subgraph Pairwise Distance Kernel
We introduce a novel graph kernel called the Neighborhood Subgraph Pairwise Distance Kernel. The kernel decomposes a graph into all pairs of neighborhood subgraphs of small radius...
Fabrizio Costa, Kurt De Grave
ICML
2010
IEEE
14 years 19 days ago
Generalizing Apprenticeship Learning across Hypothesis Classes
This paper develops a generalized apprenticeship learning protocol for reinforcementlearning agents with access to a teacher who provides policy traces (transition and reward obse...
Thomas J. Walsh, Kaushik Subramanian, Michael L. L...
ICML
2010
IEEE
14 years 19 days ago
Efficient Learning with Partially Observed Attributes
We describe and analyze efficient algorithms for learning a linear predictor from examples when the learner can only view a few attributes of each training example. This is the ca...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
ICML
2010
IEEE
14 years 19 days ago
Learning the Linear Dynamical System with ASOS
We develop a new algorithm, based on EM, for learning the Linear Dynamical System model. Called the method of Approximated Second-Order Statistics (ASOS) our approach achieves dra...
James Martens
ICML
2010
IEEE
14 years 19 days ago
Active Risk Estimation
We address the problem of evaluating the risk of a given model accurately at minimal labeling costs. This problem occurs in situations in which risk estimates cannot be obtained f...
Christoph Sawade, Niels Landwehr, Steffen Bickel, ...