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» Multiagent learning using a variable learning rate
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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
16 years 6 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
162
Voted
ISMB
1993
15 years 7 months ago
Transmembrane Segment Prediction from Protein Sequence Data
Weconsider tile automatedidentification of transmembrane domains in membrane protein sequences. 324 proteins (containing 1585 segrrmnts) werc examined, representing every protein ...
Sholom M. Weiss, Dawn M. Cohen, Nitin Indurkhya
ICCV
2009
IEEE
16 years 11 months ago
Semi-Supervised Random Forests
Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
174
Voted
NIPS
1993
15 years 7 months ago
The Power of Amnesia
We propose a learning algorithm for a variable memory length Markov process. Human communication, whether given as text, handwriting, or speech, has multi characteristic time scal...
Dana Ron, Yoram Singer, Naftali Tishby
PAMI
2008
250views more  PAMI 2008»
15 years 6 months ago
Combined Top-Down/Bottom-Up Segmentation
We construct an image segmentation scheme that combines top-down (TD) with bottom-up (BU) processing. In the proposed scheme, segmentation and recognition are intertwined rather th...
Eran Borenstein, Shimon Ullman