Thesis Information
Title: Algorithms for Large and High-Dimensional Data: Compression, Sketching and Quantization
Adviser: Piotr Indyk
Institution: MIT
Graduation Date: June 2020
Contact Information
Email Candidate
Candidate Website
SIGACT Membership No.: 8157902
Candidate Bio:
I am a PhD candidate in CSAIL, MIT, advised by Piotr Indyk. During my PhD I completed summer internships in Microsoft Research Redmond (2019), Amazon Core Machine Learning Group (2017), and VMware Research Group (2015). I received my MSc from the Weizmann Institute, and BSc in Computer Science and Mathematics from the Technion, Israel.
Paper 1:
Practical Data-Dependent Metric Compression with Provable Guarantees, Piotr Indyk, Ilya Razenshteyn and Tal Wagner, NeurIPS, 2017
Link to PDFPaper 2:
Approximate Nearest Neighbors in Limited Space, Piotr Indyk and Tal Wagner, COLT, 2018
Link to PDFPaper 3:
Semi-Supervised Learning on Data Streams via Temporal Label Propagation, Tal Wagner, Sudipto Guha, Shiva Kasiviswanathan and Nina Mishra, ICML, 2018
Link to PDFKeywords: metric spaces, sketching, quantization, nearest neighbor search, dimension reduction