| 2011 |
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| 36 | Online and Batch Learning Algorithms for Data with Missing Features. Afshin Rostamizadeh, Alekh Agarwal, Peter L. Bartlett. CoRR (abs/1104.0729) (2011). Web SearchBibTeXDownload |
| 35 | Oracle inequalities for computationally budgeted model selection. Alekh Agarwal, John C. Duchi, Peter L. Bartlett, Clement Levrard. Journal of Machine Learning Research - Proceedings Track (19): 69-86 (2011). Web SearchBibTeXDownload |
| 34 | Learning with Missing Features. Afshin Rostamizadeh, Alekh Agarwal, Peter L. Bartlett. UAI 2011, 635-642. Web SearchBibTeXDownload |
| 2010 |
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| 33 | A Learning-Based Approach to Reactive Security. Adam Barth, Benjamin I. P. Rubinstein, Mukund Sundararajan, John C. Mitchell, Dawn Song, Peter L. Bartlett. Financial Cryptography 2010, 192-206. Web SearchBibTeXDownload |
| 32 | Implicit Online Learning. Brian Kulis, Peter L. Bartlett. ICML 2010, 575-582. Web SearchBibTeXDownload |
| 31 | Optimal Allocation Strategies for the Dark Pool Problem. Alekh Agarwal, Peter L. Bartlett, Max Dama. Journal of Machine Learning Research - Proceedings Track (9): 9-16 (2010). Web SearchBibTeXDownload |
| 2009 |
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| 30 | Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning. Benjamin I. P. Rubinstein, Peter L. Bartlett, Ling Huang, Nina Taft. CoRR (abs/0911.5708) (2009). Web SearchBibTeXDownload |
| 29 | A Learning-Based Approach to Reactive Security. Adam Barth, Benjamin I. P. Rubinstein, Mukund Sundararajan, John C. Mitchell, Dawn Song, Peter L. Bartlett. CoRR (abs/0912.1155) (2009). Web SearchBibTeXDownload |
| 28 | A Stochastic View of Optimal Regret through Minimax Duality. Jacob Abernethy, Alekh Agarwal, Peter L. Bartlett, Alexander Rakhlin. CoRR (abs/0903.5328) (2009). Web SearchBibTeXDownload |
| 27 | Information-theoretic lower bounds on the oracle complexity of convex optimization. Alekh Agarwal, Peter L. Bartlett, Pradeep D. Ravikumar, Martin J. Wainwright. NIPS 2009, 1-9. Web SearchBibTeXDownload |
| 2008 |
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| 26 | Correction to "The Importance of Convexity in Learning With Squared Loss". Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson. IEEE Transactions on Information Theory (54): 4395 (2008). Web SearchBibTeXDownload |
| 2004 |
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| 25 | Learning the Kernel Matrix with Semidefinite Programming. Gert R. G. Lanckriet, Nello Cristianini, Peter L. Bartlett, Laurent El Ghaoui, Michael I. Jordan. Journal of Machine Learning Research (5): 27-72 (2004). Web SearchBibTeXDownload |
| 24 | Exponentiated Gradient Algorithms for Large-margin Structured Classification. Peter L. Bartlett, Michael Collins, Benjamin Taskar, David A. McAllester. NIPS 2004. Web SearchBibTeXDownload |
| 2003 |
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| 23 | Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates. Peter L. Bartlett, Michael I. Jordan, Jon D. McAuliffe. NIPS 2003. Web SearchBibTeXDownload |
| 2002 |
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| 22 | Learning the Kernel Matrix with Semi-Definite Programming. Gert R. G. Lanckriet, Nello Cristianini, Peter L. Bartlett, Laurent El Ghaoui, Michael I. Jordan. ICML 2002, 323-330. Web SearchBibTeX |
| 21 | Covering numbers for support vector machines. Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Robert C. Williamson. IEEE Transactions on Information Theory (48): 239-250 (2002). Web SearchBibTeXDownload |
| 20 | Generalization Error of Combined Classifiers. Llew Mason, Peter L. Bartlett, Mostefa Golea. J. Comput. Syst. Sci. (65): 415-438 (2002). Cited by 6Web SearchBibTeXDownload |
| 19 | Hardness results for neural network approximation problems. Peter L. Bartlett, Shai Ben-David. Theor. Comput. Sci. (284): 53-66 (2002). Web SearchBibTeXDownload |
| 2000 |
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| 18 | Improved Generalization Through Explicit Optimization of Margins. Llew Mason, Peter L. Bartlett, Jonathan Baxter. Machine Learning (38): 243-255 (2000). Cited by 83Web SearchBibTeXDownload |
| 17 | Learning Changing Concepts by Exploiting the Structure of Change. Peter L. Bartlett, Shai Ben-David, Sanjeev R. Kulkarni. Machine Learning (41): 153-174 (2000). Web SearchBibTeXDownload |
| 16 | New Support Vector Algorithms. Bernhard Schölkopf, Alex J. Smola, Robert C. Williamson, Peter L. Bartlett. Neural Computation (12): 1207-1245 (2000). Web SearchBibTeXDownload |
| 15 | Sparse Greedy Gaussian Process Regression. Alex J. Smola, Peter L. Bartlett. NIPS 2000, 619-625. Web SearchBibTeX |
| 1999 |
|---|
| 14 | Covering Numbers for Support Vector Machines. Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Robert C. Williamson. COLT 1999, 267-277. Web SearchBibTeXDownload |
| 13 | Hardness Results for Neural Network Approximation Problems. Peter L. Bartlett, Shai Ben-David. EuroCOLT 1999, 50-62. Web SearchBibTeXDownload |
| 12 | Boosting Algorithms as Gradient Descent. Llew Mason, Jonathan Baxter, Peter L. Bartlett, Marcus R. Frean. NIPS 1999, 512-518. Cited by 167Web SearchBibTeXDownload |
| 1998 |
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| 11 | The Importance of Convexity in Learning with Squared Loss. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson. IEEE Transactions on Information Theory (44): 1974-1980 (1998). Web SearchBibTeXDownload |
| 10 | Direct Optimization of Margins Improves Generalization in Combined Classifiers. Llew Mason, Peter L. Bartlett, Jonathan Baxter. NIPS 1998, 288-294. Cited by 34Web SearchBibTeXDownload |
| 9 | Shrinking the Tube: A New Support Vector Regression Algorithm. Bernhard Schölkopf, Peter L. Bartlett, Alex J. Smola, Robert C. Williamson. NIPS 1998, 330-336. Web SearchBibTeXDownload |
| 1997 |
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| 8 | Correction to 'Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes'. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson. Neural Computation (9): 765-769 (1997). Web SearchBibTeXDownload |
| 7 | Generalization in Decision Trees and DNF: Does Size Matter?. Mostefa Golea, Peter L. Bartlett, Wee Sun Lee, Llew Mason. NIPS 1997. Cited by 24Web SearchBibTeX |
| 1996 |
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| 6 | Learning Changing Concepts by Exploiting the Structure of Change. Peter L. Bartlett, Shai Ben-David, Sanjeev R. Kulkarni. COLT 1996, 131-139. Web SearchBibTeXDownload |
| 5 | The Importance of Convexity in Learning with Squared Loss. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson. COLT 1996, 140-146. Web SearchBibTeXDownload |
| 4 | Efficient agnostic learning of neural networks with bounded fan-in. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson. IEEE Transactions on Information Theory (42): 2118-2132 (1996). Web SearchBibTeXDownload |
| 1995 |
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| 3 | On Efficient Agnostic Learning of Linear Combinations of Basis Functions. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson. COLT 1995, 369-376. Web SearchBibTeXDownload |
| 2 | Examples of learning curves from a modified VC-formalism. Adam Kowalczyk, Jacek Szymanski, Peter L. Bartlett, Robert C. Williamson. NIPS 1995, 344-350. Web SearchBibTeXDownload |
| 1994 |
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| 1 | Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes. Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson. COLT 1994, 362-367. Web SearchBibTeXDownload |
