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» Presenting Data from Experiments in Algorithmics
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KDD
2008
ACM
161views Data Mining» more  KDD 2008»
16 years 3 months ago
Locality sensitive hash functions based on concomitant rank order statistics
: Locality Sensitive Hash functions are invaluable tools for approximate near neighbor problems in high dimensional spaces. In this work, we are focused on LSH schemes where the si...
Kave Eshghi, Shyamsundar Rajaram
KDD
2007
ACM
566views Data Mining» more  KDD 2007»
16 years 3 months ago
IMDS: intelligent malware detection system
The proliferation of malware has presented a serious threat to the security of computer systems. Traditional signature-based antivirus systems fail to detect polymorphic and new, ...
Yanfang Ye, Dingding Wang, Tao Li, Dongyi Ye
147
Voted
KDD
2007
ACM
151views Data Mining» more  KDD 2007»
16 years 3 months ago
Efficient mining of iterative patterns for software specification discovery
Studies have shown that program comprehension takes up to 45% of software development costs. Such high costs are caused by the lack-of documented specification and further aggrava...
Chao Liu 0001, David Lo, Siau-Cheng Khoo
KDD
2006
ACM
109views Data Mining» more  KDD 2006»
16 years 3 months ago
Extracting redundancy-aware top-k patterns
Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance...
Dong Xin, Hong Cheng, Xifeng Yan, Jiawei Han
143
Voted
PEPM
2009
ACM
16 years 9 days ago
Self-adjusting computation: (an overview)
Many applications need to respond to incremental modifications to data. Being incremental, such modification often require incremental modifications to the output, making it po...
Umut A. Acar
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