← Authors

Philip M. Long

26 papers · 2002–2024 · 5 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (7) πŸ—ΊοΈ Taxonomy Completionist (12) 🌈 Renaissance Researcher (5) 🧭 Keyword Pioneer πŸƒ Academic Marathon (22) πŸ”¬ Deep Specialist (13) πŸ† Keyword Champion πŸ’Ž Century Club (26) πŸ—ƒοΈ Keyword Collector (55) πŸ”₯ Unstoppable (8) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer ❓ The Questioner (2)

Conferences

JMLR (16) COLT (3) ICLR (3) ALT (2) NIPS (2)

Top co-authors

Niladri S. Chatterji (6) Peter L. Bartlett (5) David P. Helmbold (5) Rocco A. Servedio (3) Hanie Sedghi (2) Peter Bartlett (1) Raphael J. Long (1) Vineet Gupta (1) Olivier Bousquet (1) Difan Zou (1)

Keywords

learning theory (4) gradient descent (4) deep network (4) excess risk (4) benign overfitting (3) sample complexity (3) logistic loss (3) online learning (3) neural network optimization (2) pac learning (2) neural network (2) sharpness-aware minimization (2) generalization bound (2) weight decay (2) mistake bound (2) linear regression (2) dropout regularization (2) linear classifier (2) gradient flow (2) text categorization (1)

Papers

Sharpness-Aware Minimization and the Edge of Stability JMLR 2024
Deep linear networks can benignly overfit when shallow ones do JMLR 2023
The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima JMLR 2023
Foolish Crowds Support Benign Overfitting JMLR 2022
The Interplay Between Implicit Bias and Benign Overfitting in Two-Layer Linear Networks JMLR 2022
When Does Gradient Descent with Logistic Loss Find Interpolating Two-Layer Networks? JMLR 2021
Failures of Model-dependent Generalization Bounds for Least-norm Interpolation JMLR 2021
When does gradient descent with logistic loss interpolate using deep networks with smoothed ReLU activations? COLT 2021
Finite-sample Analysis of Interpolating Linear Classifiers in the Overparameterized Regime JMLR 2021
Generalization bounds for deep convolutional neural networks ICLR 2020
On the Complexity of Proper Distribution-Free Learning of Linear Classifiers ALT 2020
Learning Sums of Independent Random Variables with Sparse Collective Support JMLR 2020
On the Global Convergence of Training Deep Linear ResNets ICLR 2020
The Singular Values of Convolutional Layers ICLR 2019
Surprising properties of dropout in deep networks JMLR 2018
New bounds on the price of bandit feedback for mistake-bounded online multiclass learning ALT 2017
Surprising properties of dropout in deep networks COLT 2017
On the Inductive Bias of Dropout JMLR 2015
Algorithms and Hardness Results for Parallel Large Margin Learning JMLR 2013
On the Necessity of Irrelevant Variables JMLR 2012
New Bounds for Learning Intervals with Implications for Semi-Supervised Learning COLT 2012
Learning Halfspaces with Malicious Noise JMLR 2009
Online Learning of Multiple Tasks with a Shared Loss JMLR 2007
Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions NIPS 2006
Learnability and the doubling dimension NIPS 2006
Introduction to the Special Issue on Computational Learning Theory JMLR 2002