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Inside CMSA’s Big Data Conference: Prof. Ronitt Rubinfeld (MIT, CSAIL)
Professor Ronitt Rubinfeld discusses her research on big data and her upcoming CMSA Big Data conference talk, “Something for almost nothing: sublinear time approximation algorithms.” “Prof. Rubinfeld’s talk begins at […] ...
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Inside CMSA’s Big Data Conference: Prof. Piotr Indyk (MIT, CSAIL)
Prof. Piotr Indyk spoke to us about his work on big data and his CMSA Big Data conference talk, “Fast Algorithms for Structured Sparsity.” ...
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Inside CMSA’s Big Data Conference: Prof. Lucy Colwell (University of Cambridge)
Prof. Lucy Colwell spoke with us about her CMSA Big Data conference talk, “Using evolutionary sequence variation to make inferences about protein structure and function: Modeling with Random Matrix Theory,” […] ...
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Inside CMSA’s Big Data Conference: Prof. Michael Jordan (UC Berkeley)
Prof. Michael Jordan talks to us about his work on big data and his talk at CMSA’s big data conference, “Computational thinking, inferential thinking and Big Data.” ...
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Inside CMSA’s Big Data Conference: Prof. Gunnar Carlsson (Stanford & Ayasdi)
Professor Gunnar Carlsson spoke to us about his CMSA Big Data Conference talk, “Persistent homology for qualitative analysis and feature generation,” and his research and work on big data. ...
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Inside CMSA’s Big Data Conference: Prof. Susan Athey (Stanford)
Professor Susan Athey discusses her research on big data and machine learning, and her CMSA Big Data conference talk, “Machine Learning and Causal Inference for Policy Evaluation.” Her talk discusses […] ...
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Inside CMSA’s Big Data Conference: Prof. Ryan Adams (Twitter Cortex & Harvard University)
Professor Ryan Adams on his CMSA Big Data conference talk, “Exact Markov Chain Monte Carlo with Large Data.” ...
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Inside CMSA’s Big Data Conference: Prof. Jelani Nelson (Harvard University)
Professor Jelani Nelson sat down with us to discuss his upcoming talk at CMSA’s Big Data conference. His talk is titled, “Dimensionality reductions via sparse matrices,” and will take place […] ...
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