Philip Long
Philip Long
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Breast cancer classification and prognosis based on gene expression profiles from a population-based study
C Sotiriou, SY Neo, LM McShane, EL Korn, PM Long, A Jazaeri, P Martiat, ...
Proceedings of the National Academy of Sciences 100 (18), 10393-10398, 2003
Benign overfitting in linear regression
PL Bartlett, PM Long, G Lugosi, A Tsigler
Proceedings of the National Academy of Sciences 117 (48), 30063-30070, 2020
Comparative full-length genome sequence analysis of 14 SARS coronavirus isolates and common mutations associated with putative origins of infection
YJ Ruan, CL Wei, AE Ling, VB Vega, H Thoreau, SYS Thoe, JM Chia, ...
The Lancet 361 (9371), 1779-1785, 2003
Comment on"'Stemness': transcriptional profiling of embryonic and adult stem cells" and" a stem cell molecular signature"(I)
NO Fortunel, HH Otu, HH Ng, J Chen, X Mu, T Chevassut, X Li, M Joseph, ...
Science 302 (5644), 393-393, 2003
Performance guarantees for hierarchical clustering
S Dasgupta, PM Long
Journal of Computer and System Sciences 70 (4), 555-569, 2005
Random classification noise defeats all convex potential boosters
PM Long, RA Servedio
Proceedings of the 25th international conference on Machine learning, 608-615, 2008
The relaxed online maximum margin algorithm
Y Li, P Long
Advances in neural information processing systems 12, 1999
Tracking drifting concepts by minimizing disagreements
DP Helmbold, PM Long
Machine learning 14, 27-45, 1994
Reinforcement learning with immediate rewards and linear hypotheses
N Abe, AW Biermann, PM Long
Algorithmica 37, 263-293, 2003
Improved bounds on the sample complexity of learning
Y Li, PM Long, A Srinivasan
Journal of Computer and System Sciences 62 (3), 516-527, 2001
Worst-case quadratic loss bounds for prediction using linear functions and gradient descent
N Cesa-Bianchi, PM Long, MK Warmuth
IEEE Transactions on Neural Networks 7 (3), 604-619, 1996
Fat-shattering and the learnability of real-valued functions
PL Bartlett, PM Long, RC Williamson
Proceedings of the seventh annual conference on Computational learning†…, 1994
On the difficulty of approximately maximizing agreements
S Ben-David, N Eiron, PM Long
Journal of Computer and System Sciences 66 (3), 496-514, 2003
The singular values of convolutional layers
H Sedghi, V Gupta, PM Long
arXiv preprint arXiv:1805.10408, 2018
Optimal gene expression analysis by microarrays
LD Miller, PM Long, L Wong, S Mukherjee, LM McShane, ET Liu
Cancer cell 2 (5), 353-361, 2002
The power of localization for efficiently learning linear separators with noise
P Awasthi, MF Balcan, PM Long
Journal of the ACM (JACM) 63 (6), 1-27, 2017
Molecular changes from dysplastic nodule to hepatocellular carcinoma through gene expression profiling
SW Nam, JY Park, A Ramasamy, S Shevade, A Islam, PM Long, CK Park, ...
Hepatology 42 (4), 809-818, 2005
Characterizations of Learnability for Classes of {0,..., n}-Valued Functions
S Bendavid, N Cesabianchi, D Haussler, PM Long
Journal of Computer and System Sciences 50 (1), 74-86, 1995
Active and passive learning of linear separators under log-concave distributions
MF Balcan, P Long
Conference on Learning Theory, 288-316, 2013
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
P Bartlett, D Helmbold, P Long
International conference on machine learning, 521-530, 2018
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