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ACL
2009
15 years 4 months ago
Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Yoshimasa Tsuruoka, Jun-ichi Tsujii, Sophia Anania...
CVPR
2005
IEEE
16 years 8 months ago
Combining Object and Feature Dynamics in Probabilistic Tracking
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
EMMCVPR
2005
Springer
16 years 10 days ago
Optimizing the Cauchy-Schwarz PDF Distance for Information Theoretic, Non-parametric Clustering
This paper addresses the problem of efficient information theoretic, non-parametric data clustering. We develop a procedure for adapting the cluster memberships of the data pattern...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...
ISMIR
2005
Springer
154views Music» more  ISMIR 2005»
16 years 9 days ago
Exploiting the Tradeoff Between Precision and Cpu-Time to Speed Up Nearest Neighbor Search
We describe a recursive algorithm to quickly compute the N nearest neighbors according to a similarity measure in a metric space. The algorithm exploits an intrinsic property of a...
Pierre Roy, Jean-Julien Aucouturier, Franço...
FOCS
2007
IEEE
16 years 1 months ago
Adaptive Simulated Annealing: A Near-optimal Connection between Sampling and Counting
We present a near-optimal reduction from approximately counting the cardinality of a discrete set to approximately sampling elements of the set. An important application of our wo...
Daniel Stefankovic, Santosh Vempala, Eric Vigoda