Showing 1–20 of 20 results
/ Date/ Name
Jul 20, 2025eMargin: Revisiting Contrastive Learning with Margin-Based SeparationOct 20, 2024Contrast All the Time: Learning Time Series Representation from Temporal ConsistencyJan 3, 2022Execute Order 66: Targeted Data Poisoning for Reinforcement LearningDec 5, 2021Probabilistic Deep Learning to Quantify Uncertainty in Air Quality ForecastingJan 20, 2021LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial RecognitionOct 19, 2020Robust Optimization as Data Augmentation for Large-scale GraphsOct 8, 2020Information-Driven Adaptive Sensing Based on Deep Reinforcement LearningSep 4, 2020Witches' Brew: Industrial Scale Data Poisoning via Gradient MatchingApr 1, 2020MetaPoison: Practical General-purpose Clean-label Data PoisoningMay 15, 2019Transferable Clean-Label Poisoning Attacks on Deep Neural NetsApr 29, 2019Adversarial Training for Free!Dec 28, 2017Visualizing the Loss Landscape of Neural NetsJun 9, 2017Adaptive Consensus ADMM for Distributed OptimizationMay 6, 2016Training Neural Networks Without Gradients: A Scalable ADMM ApproachDec 5, 2015Variance Reduction for Distributed Stochastic Gradient DescentOct 15, 2015Layer-Specific Adaptive Learning Rates for Deep NetworksApr 8, 2015Unwrapping ADMM: Efficient Distributed Computing via Transpose ReductionApr 16, 2014An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation AccuracyOct 16, 2012Value Function Approximation in Noisy Environments Using Locally Smoothed Regularized Approximate Linear ProgramsMay 11, 2010Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes