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» Evaluating algorithms that learn from data streams
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AAAI
2008
15 years 9 months ago
Semi-supervised Classification Using Local and Global Regularization
In this paper, we propose a semi-supervised learning (SSL) algorithm based on local and global regularization. In the local regularization part, our algorithm constructs a regular...
Fei Wang, Tao Li, Gang Wang, Changshui Zhang
207
Voted
ICMCS
2008
IEEE
206views Multimedia» more  ICMCS 2008»
16 years 1 months ago
Redundant motion vectors for improved error resilience in H.264/AVC coded video
This proposal presents a new error robust strategy for encoding redundant pictures for the H.264/AVC standard. The method is based on providing motion vectors as redundant data, i...
Maheshi B. Dissanayake, Chaminda T. E. R. Hewage, ...
DEBS
2010
ACM
15 years 10 months ago
Predictive publish/subscribe matching
A new publish/subscribe capability is presented: the ability to predict the likelihood that a subscription will be matched at some point in the future. Composite subscriptions con...
Vinod Muthusamy, Haifeng Liu, Hans-Arno Jacobsen
145
Voted
SIGCSE
1997
ACM
121views Education» more  SIGCSE 1997»
15 years 11 months ago
Application-based modules using apprentice learning for CS 2
A typical Data Structures (CS 2) course covers a wide variety of topics: elementary algorithm analysis; data structures including dynamic structures, trees, tables, graphs, etc.; ...
Owen L. Astrachan, Robert F. Smith, James T. Wilke...
190
Voted
DAGSTUHL
2007
15 years 8 months ago
Learning Probabilistic Relational Dynamics for Multiple Tasks
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...