283 citations · 588 across the 29 of their papers we have counts for
5 papers · 1 filter
Overcoming Catastrophic Forgetting via Direction-Constrained Optimization
Yunfei Teng, Anna Choromanska, Murray Campbell +3
This paper studies a new design of the optimization algorithm for training deep learning models with a fixed architecture of the classification network in a continual learning fram…
Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations
Pu Zhao, Parikshit Ram, Songtao Lu +4
Adversarial perturbations are critical for certifying the robustness of deep learning models. A universal adversarial perturbation (UAP) can simultaneously attack multiple images,…
Neural Neighborhood Encoding for Classification
Kaushik Sinha, Parikshit Ram
Inspired by the fruit-fly olfactory circuit, the Fly Bloom Filter [Dasgupta et al., 2018] is able to efficiently summarize the data with a single pass and has been used for novelty…
Solving Constrained CASH Problems with ADMM
Parikshit Ram, Sijia Liu, Deepak Vijaykeerthi +5
The CASH problem has been widely studied in the context of automated configurations of machine learning (ML) pipelines and various solvers and toolkits are available. However, CASH…
Lale: Consistent Automated Machine Learning
Guillaume Baudart, Martin Hirzel, Kiran Kate +2
Automated machine learning makes it easier for data scientists to develop pipelines by searching over possible choices for hyperparameters, algorithms, and even pipeline topologies…