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» Using Problems to Learn Service-Oriented Computing
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NPC
2007
Springer
15 years 11 months ago
A Cost-Aware Parallel Workload Allocation Approach Based on Machine Learning Techniques
Parallelism is one of the main sources for performance improvement in modern computing environment, but the efficient exploitation of the available parallelism depends on a number ...
Shun Long, Grigori Fursin, Björn Franke
ICDM
2010
IEEE
122views Data Mining» more  ICDM 2010»
15 years 2 months ago
Learning Preferences with Millions of Parameters by Enforcing Sparsity
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G....
ICALP
2011
Springer
14 years 8 months ago
New Algorithms for Learning in Presence of Errors
We give new algorithms for a variety of randomly-generated instances of computational problems using a linearization technique that reduces to solving a system of linear equations...
Sanjeev Arora, Rong Ge
SIGCSE
2009
ACM
169views Education» more  SIGCSE 2009»
16 years 5 months ago
The impact of instructor initiative on student learning: a tutoring study
In the quest to find instructional approaches that benefit student learning, engagement, and retention, evidence suggests providing students with hands-on practice is a worthwhile...
Kristy Elizabeth Boyer, Robert Phillips, Michael D...
IJCV
2010
158views more  IJCV 2010»
15 years 3 months ago
Metric Learning for Image Alignment
Abstract Image alignment has been a long standing problem in computer vision. Parameterized Appearance Models (PAMs) such as the Lucas-Kanade method, Eigentracking, and Active Appe...
Minh Hoai Nguyen, Fernando De la Torre