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USS
2010
14 years 7 months ago
P4P: Practical Large-Scale Privacy-Preserving Distributed Computation Robust against Malicious Users
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
Yitao Duan, NetEase Youdao, John Canny, Justin Z. ...
108
Voted
KDD
2009
ACM
611views Data Mining» more  KDD 2009»
15 years 10 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
AAAI
1994
14 years 11 months ago
Solution Reuse in Dynamic Constraint Satisfaction Problems
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
Gérard Verfaillie, Thomas Schiex
113
Voted
COORDINATION
2009
Springer
15 years 10 months ago
Enhanced Coordination in Sensor Networks through Flexible Service Provisioning
: Heterogeneous wireless sensor networks represent a challenging programming environment. Servilla addresses this by offering a new middleware framework that provides service provi...
Chien-Liang Fok, Gruia-Catalin Roman, Chenyang Lu
89
Voted
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
15 years 10 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...