Hristo Paskov

I'm a fifth year PhD student in Stanford's Computer Science department. My research interests span machine learning, optimization, and algorithms. My advisors are John Mitchell and Trevor Hastie.

Previously, I did my BS and Master's at MIT under Tomaso Poggio and David Brock.


I'm on the job market. If you're interested please feel free to send me an email (address is in the CV). My application materials: CV, research statement, and teaching statement.


Data Representation and Compression Using Linear-Programming Approximations. Hristo Paskov, John Mitchell, Trevor Hastie. ICLR, 2016.

Fast Algorithms for Learning with Long N-Grams via Suffix Tree Based Matrix Multiplication. Hristo Paskov, John Mitchell, Trevor Hastie. Uncertainty in Artificial Intelligence, 2015. Supplementary Material.

Exploiting Social Network Structure for Person-to-Person Sentiment Analysis. Robert West, Hristo Paskov, Jure Leskovec, Christopher Potts. Transactions of the Association for Computational Linguistics, 2(Oct), pages 297:310, 2014.

An Efficient Algorithm for Large Scale Compressive Feature Learning. Hristo Paskov, John Mitchell, Trevor Hastie. AISTATS, pages 760-768, 2014. Supplementary Material.

Joint learning over drugs improves prediction of cancer drug response. Ivan Paskov, Han Yuan, Hristo Paskov, Alvaro Gonzalez, Christina Leslie. RECOMB/ISCB Conference on Regulatory and Systems Genomics, Abstract and Oral Presentation, 2014.

Compressive Feature Learning. Hristo Paskov, Robert West, John Mitchell, Trevor Hastie. Neural Information Processing Systems, pages 2931-2939, 2013. Supplementary Material.

On the Feasibility of Internet-Scale Author Identification. Arvind Narayanan, Hristo Paskov, Neil Zhenqiang Gong, John Bethencourt, Emil Stefanov, Eui Chul Richard Shin, and Dawn Song. IEEE Symposium on Security and Privacy, pages 300-314, IEEE Computer Society, 2012.

The Failure of Noise-Based Non-continuous Audio Captchas. Elie Bursztein, Romain Beauxis, Hristo Paskov, Daniele Perito, Celine Fabry, and John Mitchell. IEEE Symposium on Security and Privacy, pages 19-31, IEEE Computer Society, 2011.


A Regularization Framework for Active Learning from Imbalanced Data. MIT Master's Thesis, 2010.

Accessing Wikipedia. MIT Undergraduate Senior Thesis, 2008.