Daniel Hsu

UCSD

other persons with the same name:

• Daniel Hsu

	2012
33		Animashree Anandkumar, Daniel Hsu, Sham M. Kakade: A Method of Moments for Mixture Models and Hidden Markov Models CoRR abs/1203.0683: (2012)
32		Animashree Anandkumar, Daniel Hsu, Sham M. Kakade: Learning High-Dimensional Mixtures of Graphical Models CoRR abs/1203.0697: (2012)
31		Kamalika Chaudhuri, Yoav Freund, Daniel Hsu: An Online Learning-based Framework for Tracking CoRR abs/1203.3471: (2012)
30		Animashree Anandkumar, Dean P. Foster, Daniel Hsu, Sham M. Kakade, Yi-Kai Liu: Two SVDs Suffice: Spectral decompositions for probabilistic topic modeling and latent Dirichlet allocation CoRR abs/1204.6703: (2012)
	2011
29		Alekh Agarwal, Dean P. Foster, Daniel Hsu, Sham M. Kakade, Alexander Rakhlin: Stochastic convex optimization with bandit feedback. NIPS 2011: 1035-1043
28		Animashree Anandkumar, Kamalika Chaudhuri, Daniel Hsu, Sham M. Kakade, Le Song, Tong Zhang: Spectral Methods for Learning Multivariate Latent Tree Structure. NIPS 2011: 2025-2033
27		Miroslav Dudík, Daniel Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang: Efficient Optimal Learning for Contextual Bandits. UAI 2011: 169-178
26		Daniel Hsu, Nikos Karampatziakis, John Langford, Alexander J. Smola: Parallel Online Learning CoRR abs/1103.4204: (2011)
25		Daniel Hsu, Sham M. Kakade, Tong Zhang: An Analysis of Random Design Linear Regression CoRR abs/1106.2363: (2011)
24		Miroslav Dudík, Daniel Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang: Efficient Optimal Learning for Contextual Bandits CoRR abs/1106.2369: (2011)
23		Animashree Anandkumar, Kamalika Chaudhuri, Daniel Hsu, Sham M. Kakade, Le Song, Tong Zhang: Spectral Methods for Learning Multivariate Latent Tree Structure CoRR abs/1107.1283: (2011)
22		Alekh Agarwal, Dean P. Foster, Daniel Hsu, Sham M. Kakade, Alexander Rakhlin: Stochastic convex optimization with bandit feedback CoRR abs/1107.1744: (2011)
21		Daniel Hsu, Sham M. Kakade, Tong Zhang: A tail inequality for quadratic forms of subgaussian random vectors CoRR abs/1110.2842: (2011)
20		Daniel Hsu, Sham M. Kakade, Tong Zhang: Robust Matrix Decomposition With Sparse Corruptions. IEEE Transactions on Information Theory 57(11): 7221-7234 (2011)
19		Kamalika Chaudhuri, Daniel Hsu: Sample Complexity Bounds for Differentially Private Learning. Journal of Machine Learning Research - Proceedings Track 19: 155-186 (2011)
	2010
18		Alina Beygelzimer, Daniel Hsu, John Langford, Tong Zhang: Agnostic Active Learning Without Constraints. NIPS 2010: 199-207
17		Kamalika Chaudhuri, Yoav Freund, Daniel Hsu: An Online Learning-based Framework for Tracking. UAI 2010: 101-108
16		Alina Beygelzimer, Daniel Hsu, John Langford, Tong Zhang: Agnostic Active Learning Without Constraints CoRR abs/1006.2588: (2010)
15		Daniel Hsu, Sham M. Kakade, Tong Zhang: Robust Matrix Decomposition with Outliers CoRR abs/1011.1518: (2010)
	2009
14		Daniel Hsu, Sham M. Kakade, Tong Zhang: A Spectral Algorithm for Learning Hidden Markov Models. COLT 2009
13		Kamalika Chaudhuri, Yoav Freund, Daniel Hsu: A Parameter-free Hedging Algorithm. NIPS 2009: 297-305
12		Daniel Hsu, Sham Kakade, John Langford, Tong Zhang: Multi-Label Prediction via Compressed Sensing. NIPS 2009: 772-780
11		Daniel Hsu, Sham M. Kakade, John Langford, Tong Zhang: Multi-Label Prediction via Compressed Sensing CoRR abs/0902.1284: (2009)
10		Kamalika Chaudhuri, Yoav Freund, Daniel Hsu: A parameter-free hedging algorithm CoRR abs/0903.2851: (2009)
9		Kamalika Chaudhuri, Yoav Freund, Daniel Hsu: Tracking using explanation-based modeling CoRR abs/0903.2862: (2009)
	2008
8		Sanjoy Dasgupta, Daniel Hsu: Hierarchical sampling for active learning. ICML 2008: 208-215
7		Sanjoy Dasgupta, Daniel Hsu, Claire Monteleoni: A General Agnostic Active Learning Algorithm. ISAIM 2008
6		Yoav Freund, Daniel Hsu: A new Hedging algorithm and its application to inferring latent random variables CoRR abs/0806.4802: (2008)
5		Daniel Hsu, Sham M. Kakade, Tong Zhang: A Spectral Algorithm for Learning Hidden Markov Models CoRR abs/0811.4413: (2008)
	2007
4		Sanjoy Dasgupta, Daniel Hsu: On-Line Estimation with the Multivariate Gaussian Distribution. COLT 2007: 278-292
3		Sanjoy Dasgupta, Daniel Hsu, Claire Monteleoni: A general agnostic active learning algorithm. NIPS 2007
	2006
2		Sanjoy Dasgupta, Daniel Hsu, Nakul Verma: A Concentration Theorem for Projections. UAI 2006
	2004
1		Anind K. Dey, Raffay Hamid, Chris Beckmann, Ian Li, Daniel Hsu: a CAPpella: programming by demonstration of context-aware applications. CHI 2004: 33-40

Coauthor Index

1	Alekh Agarwal	[22] [29]
2	Animashree Anandkumar	[23] [28] [30] [32] [33]
3	Chris Beckmann	[1]
4	Alina Beygelzimer	[16] [18]
5	Kamalika Chaudhuri	[9] [10] [13] [17] [19] [23] [28] [31]
6	Sanjoy Dasgupta	[2] [3] [4] [7] [8]
7	Anind K. Dey	[1]
8	Miroslav Dudík	[24] [27]
9	Dean P. Foster	[22] [29] [30]
10	Yoav Freund	[6] [9] [10] [13] [17] [31]
11	Raffay Hamid	[1]
12	Sham M. Kakade (Sham Kakade)	[5] [11] [12] [14] [15] [20] [21] [22] [23] [25] [28] [29] [30] [32] [33]
13	Satyen Kale	[24] [27]
14	Nikos Karampatziakis	[24] [26] [27]
15	John Langford	[11] [12] [16] [18] [24] [26] [27]
16	Ian Li	[1]
17	Yi-Kai Liu	[30]
18	Claire Monteleoni	[3] [7]
19	Alexander Rakhlin	[22] [29]
20	Lev Reyzin	[24] [27]
21	Alexander J. Smola (Alex J. Smola)	[26]
22	Le Song	[23] [28]
23	Nakul Verma	[2]
24	Tong Zhang	[5] [11] [12] [14] [15] [16] [18] [20] [21] [23] [24] [25] [27] [28]

Colors in the list of coauthors

Last update Thu May 31 18:55:10 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page