Daniel Hsu
Department of Statistics, Rutgers University
Statistics Department, University of Pennsylvania
E-mail: <my username>@rci.rutgers.edu
Office: 467 Hill Center (Rutgers); 414.1 Huntsman Hall (UPenn)
Research papers
Alina Beygelzimer, Daniel Hsu, John Langford, and Tong Zhang.
Agnostic active learning without constraints.
Advances in Neural Information Processing Systems 23, 2010.
[arxiv]
Kamalika Chaudhuri, Yoav Freund, and Daniel Hsu. An online learning-based framework for tracking. Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, 2010.
[pdf]
Daniel Hsu, Sham M. Kakade, John Langford, and Tong Zhang. Multi-label prediction via compressed sensing. Advances in Neural Information Processing Systems 22, 2009.
[pdf, talk slides]
Kamalika Chaudhuri, Yoav Freund, and Daniel Hsu. A parameter-free hedging algorithm. Advances in Neural Information Processing Systems 22, 2009.
[pdf]
Daniel Hsu, Sham M. Kakade, and Tong Zhang. A spectral algorithm for learning hidden Markov models. Twenty-Second Annual Conference on Learning Theory, 2009.
[pdf, talk slides]
Sanjoy Dasgupta and Daniel Hsu. Hierarchical sampling for active learning. Twenty-Fifth International Conference on Machine Learning, 2008.
[pdf]
Sanjoy Dasgupta, Daniel Hsu, and Claire Monteleoni. A general agnostic active learning algorithm. Advances in Neural Information Processing Systems 20, 2007.
[pdf]
Sanjoy Dasgupta and Daniel Hsu. On-line estimation with the multivariate Gaussian distribution. Twentieth Annual Conference on Learning Theory, 2007.
[pdf]
Sanjoy Dasgupta, Daniel Hsu, and Nakul Verma. A concentration theorem for projections. Twenty-Second Conference on Uncertainty in Artificial Intelligence, 2006.
[pdf]