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TIP
2010
155views more  TIP 2010»
15 years 5 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
CORR
2010
Springer
163views Education» more  CORR 2010»
15 years 5 months ago
Faster Rates for training Max-Margin Markov Networks
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
ICML
2004
IEEE
16 years 7 months ago
Large margin hierarchical classification
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Ofer Dekel, Joseph Keshet, Yoram Singer
ISCAS
2006
IEEE
96views Hardware» more  ISCAS 2006»
16 years 26 days ago
Approximately linear-phase recursive digital filters with variable magnitude characteristics
Abstract— This paper considers designing in the minimax sense complementary low-pass/high-pass approximately linear-phase recursive filters with variable magnitude characteristi...
Juha Yli-Kaakinen, Tapio Saramäki
MICRO
2006
IEEE
73views Hardware» more  MICRO 2006»
16 years 25 days ago
Merging Head and Tail Duplication for Convergent Hyperblock Formation
VLIW and EDGE (Explicit Data Graph Execution) architectures rely on compilers to form high-quality hyperblocks for good performance. These compilers typically perform hyperblock f...
Bertrand A. Maher, Aaron Smith, Doug Burger, Kathr...