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ICML
2002
IEEE
14 years 9 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
SIGIR
2008
ACM
13 years 8 months ago
Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization
Multi-document summarization aims to create a compressed summary while retaining the main characteristics of the original set of documents. Many approaches use statistics and mach...
Dingding Wang, Tao Li, Shenghuo Zhu, Chris H. Q. D...
VLDB
2004
ACM
186views Database» more  VLDB 2004»
14 years 2 months ago
Indexing Large Human-Motion Databases
Data-driven animation has become the industry standard for computer games and many animated movies and special effects. In particular, motion capture data recorded from live actor...
Eamonn J. Keogh, Themis Palpanas, Victor B. Zordan...
AIPS
2008
13 years 11 months ago
Stochastic Enforced Hill-Climbing
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
Jia-Hong Wu, Rajesh Kalyanam, Robert Givan
ECCV
2004
Springer
14 years 10 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...