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» Randomized Algorithms and Complexity Theory
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155
Voted
KDD
2009
ACM
611views Data Mining» more  KDD 2009»
16 years 3 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
118
Voted
HPCA
2007
IEEE
16 years 3 months ago
HARD: Hardware-Assisted Lockset-based Race Detection
The emergence of multicore architectures will lead to an increase in the use of multithreaded applications that are prone to synchronization bugs, such as data races. Software sol...
Pin Zhou, Radu Teodorescu, Yuanyuan Zhou
152
Voted
ICALP
2009
Springer
16 years 3 months ago
Annotations in Data Streams
The central goal of data stream algorithms is to process massive streams of data using sublinear storage space. Motivated by work in the database community on outsourcing database...
Amit Chakrabarti, Graham Cormode, Andrew McGregor
116
Voted
AAAI
1998
15 years 4 months ago
Fast Probabilistic Modeling for Combinatorial Optimization
Probabilistic models have recently been utilized for the optimization of large combinatorial search problems. However, complex probabilistic models that attempt to capture interpa...
Shumeet Baluja, Scott Davies
122
Voted
AAAI
1996
15 years 4 months ago
Improved Limited Discrepancy Search
We present an improvement to Harvey and Ginsberg's limited discrepancy search algorithm, which eliminates much of the redundancy in the original, by generating each path from...
Richard E. Korf