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UID:www.tcs.tifr.res.in/event/1615
DTSTAMP:20251001T063421Z
SUMMARY:Faster and Space Efficient Indexing for Locality Sensitive Hashing
DESCRIPTION:Speaker: Rameshwar Pratap (IIT Hyderabad)\n\nAbstract: \nThis w
 ork suggests faster and space-efficient index construction algorithms for 
 LSH for Euclidean distance (a.k.a. E2LSH) and cosine similarity (a.k.a. SR
 P). The index construction step of these algorithms relies on grouping dat
 a points into several bins of hash tables based on their hashcode. To gene
 rate an m-dimensional hashcode of the d-dimensional data point\, these LSH
 s first project the data point onto a d-dimensional random Gaussian vector
  and then discretise the resulting inner product. The time and space compl
 exity of both E2LSH and SRP for computing an m-sized hashcode of a d-dimen
 sional vector is O(md)\, which becomes impractical for large values of m a
 nd d. To overcome this problem\, we propose  LSH algorithms for both Eucl
 idean distance and cosine similarity that  reduce the hashcode computatio
 n time from O(md) to O(d)\, and simultaneously reduce the space complexity
  from O(md) to O(d). Our proposals are backed by mathematical guarantees\,
  and we validate their performance through numerical simulations on variou
 s real-world datasets.\nShort Bio:\nDr. Rameshwar Pratap is a faculty memb
 er at Department of CSE\, IIT Hyderabad. He earned his Ph.D. in Theoretica
 l Computer Science from Chennai Mathematical Institute (CMI). His research
  work lies in the intersection of theory and practice. Broadly his researc
 h work falls in the areas of "Algorithms for Massive Datasets"\, and focus
 es on developing  dimensionality reduction algorithms and sampling algori
 thms to handle the large dimensionality and volume of the datasets\, respe
 ctively. \n \n
URL:https://www.tcs.tifr.res.in/web/events/1615
DTSTART;TZID=Asia/Kolkata:20251014T160000
DTEND;TZID=Asia/Kolkata:20251014T170000
LOCATION:A-201 (STCS Seminar Room)
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