Bhavya Kailkhura

Proceedings of the Forty-first International Conference on Machine Learning, 2024

NEFTune: Noisy Embeddings Improve Instruction Finetuning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training.

[BibT_eX]

[DOI]

Konstantinos Parasyris

Proceedings of the Twelfth International Conference on Learning Representations, 2024

SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Leveraging Hierarchical Feature Sharing for Efficient Dataset Condensation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2024, 2024

RankMean: Module-Level Importance Score for Merging Fine-tuned LLM Models.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

An accelerated proximal algorithm for regularized nonconvex and nonsmooth bi-level optimization.

[BibT_eX]

[DOI]

Ziyi Chen

Yi Zhou

Mach. Learn., May, 2023

Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities.

[BibT_eX]

[DOI]

Brian R. Bartoldson

Davis W. Blalock

J. Mach. Learn. Res., 2023

Scaling Compute Is Not All You Need for Adversarial Robustness.

[BibT_eX]

[DOI]

Edoardo Debenedetti

Zishen Wan

Maksym Andriushchenko

Vikash Sehwag

Kshitij Bhardwaj

CoRR, 2023

When Bio-Inspired Computing meets Deep Learning: Low-Latency, Accurate, & Energy-Efficient Spiking Neural Networks from Artificial Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

Pursing the Sparse Limitation of Spiking Deep Learning Structures.

[BibT_eX]

[DOI]

CoRR, 2023

Instance-wise Linearization of Neural Network for Model Interpretation.

[BibT_eX]

[DOI]

CoRR, 2023

Gaining the Sparse Rewards by Exploring Binary Lottery Tickets in Spiking Neural Network.

[BibT_eX]

[DOI]

CoRR, 2023

Shifting Attention to Relevance: Towards the Uncertainty Estimation of Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

Improving Diversity with Adversarially Learned Transformations for Domain Generalization.

[BibT_eX]

[DOI]

Tejas Gokhale

James Daniel Diffenderfer

Chitta Baral

Yezhou Yang

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Neural Image Compression: Generalization, Robustness, and Spectral Biases.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Less is More: Data Pruning for Faster Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the Workshop on Artificial Intelligence Safety 2023 (SafeAI 2023) co-located with the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), 2023

2022

Robust Decentralized Learning Using ADMM With Unreliable Agents.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2022

Representing Polymers as Periodic Graphs with Learned Descriptors for Accurate Polymer Property Predictions.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2022

Enabling machine learning-ready HPC ensembles with Merlin.

[BibT_eX]

[DOI]

Future Gener. Comput. Syst., 2022

Efficient Multi-Prize Lottery Tickets: Enhanced Accuracy, Training, and Inference Speed.

[BibT_eX]

[DOI]

CoRR, 2022

On Certifying and Improving Generalization to Unseen Domains.

[BibT_eX]

[DOI]

CoRR, 2022

"Understanding Robustness Lottery": A Comparative Visual Analysis of Neural Network Pruning Approaches.

[BibT_eX]

[DOI]

Valerio Pascucci

CoRR, 2022

Zeroth-Order SciML: Non-intrusive Integration of Scientific Software with Deep Learning.

[BibT_eX]

[DOI]

Anna Maria Hiszpanski

Mingyi Hong

CoRR, 2022

A Fast and Convergent Proximal Algorithm for Regularized Nonconvex and Nonsmooth Bi-level Optimization.

[BibT_eX]

[DOI]

Ziyi Chen

Yi Zhou

CoRR, 2022

COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks.

[BibT_eX]

[DOI]

Krishnaram Kenthapadi

Ding Zhao

Bo Li

CoRR, 2022

Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions.

[BibT_eX]

[DOI]

CoRR, 2022

More or Less (MoL): Defending against Multiple Perturbation Attacks on Deep Neural Networks through Model Ensemble and Compression.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2022

Models Out of Line: A Fourier Lens on Distribution Shift Robustness.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Benchmarking Test-Time Unsupervised Deep Neural Network Adaptation on Edge Devices.

[BibT_eX]

[DOI]

Proceedings of the International IEEE Symposium on Performance Analysis of Systems and Software, 2022

On the Certified Robustness for Ensemble Models and Beyond.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks.

[BibT_eX]

[DOI]

Krishnaram Kenthapadi

Ding Zhao

Bo Li

Proceedings of the Tenth International Conference on Learning Representations, 2022

A Spectral View of Randomized Smoothing Under Common Corruptions: Benchmarking and Improving Certified Robustness.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

Fault-Tolerant Deep Neural Networks for Processing-In-Memory based Autonomous Edge Systems.

[BibT_eX]

[DOI]

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

Unsupervised Test-Time Adaptation of Deep Neural Networks at the Edge: A Case Study.

[BibT_eX]

[DOI]

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

2021

Coverage-Based Designs Improve Sample Mining and Hyperparameter Optimization.

[BibT_eX]

[DOI]

Gowtham Muniraju

Cihan Tepedelenlioglu

Andreas Spanias

IEEE Trans. Neural Networks Learn. Syst., 2021

MR-GAN: Manifold Regularized Generative Adversarial Networks for Scientific Data.

[BibT_eX]

[DOI]

SIAM J. Math. Data Sci., 2021

Preventing Failures by Dataset Shift Detection in Safety-Critical Graph Applications.

[BibT_eX]

[DOI]

Hoseung Song

Frontiers Artif. Intell., 2021

Editorial: Safe and Trustworthy Machine Learning.

[BibT_eX]

[DOI]

Frontiers Big Data, 2021

Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselines.

[BibT_eX]

[DOI]

CoRR, 2021

Reliable Graph Neural Network Explanations Through Adversarial Training.

[BibT_eX]

[DOI]

CoRR, 2021

Mixture of Robust Experts (MoRE): A Flexible Defense Against Multiple Perturbations.

[BibT_eX]

[DOI]

CoRR, 2021

Robusta: Robust AutoML for Feature Selection via Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Deep kernels with probabilistic embeddings for small-data learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Winning Hand: Compressing Deep Networks Can Improve Out-of-Distribution Robustness.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing.

[BibT_eX]

[DOI]

Proceedings of the IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems, 2021

Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network.

[BibT_eX]

[DOI]

James Diffenderfer

Proceedings of the 9th International Conference on Learning Representations, 2021

Can Shape Structure Features Improve Model Robustness under Diverse Adversarial Settings?

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

How Robust Are Randomized Smoothing Based Defenses to Data Poisoning?

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Scalability vs. Utility: Do We Have To Sacrifice One for the Other in Data Importance Quantification?

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

TSS: Transformation-Specific Smoothing for Robustness Certification.

[BibT_eX]

[DOI]

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Attribute-Guided Adversarial Training for Robustness to Natural Perturbations.

[BibT_eX]

[DOI]

Tejas Gokhale

Chitta Baral

Yezhou Yang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2020

Automated Identification of Molecular Crystals' Packing Motifs.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2020

Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2020

MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2020

Leveraging Uncertainty from Deep Learning for Trustworthy Materials Discovery Workflows.

[BibT_eX]

[DOI]

Jize Zhang

Thomas Yong-Jin Han

CoRR, 2020

Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Explainable Deep Learning for Uncovering Actionable Scientific Insights for Materials Discovery and Design.

[BibT_eX]

[DOI]

CoRR, 2020

Actionable Attribution Maps for Scientific Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2020

A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Anomalous Instance Detection in Deep Learning: A Survey.

[BibT_eX]

[DOI]

CoRR, 2020

Automatic Perturbation Analysis on General Computational Graphs.

[BibT_eX]

[DOI]

CoRR, 2020

Anomalous Example Detection in Deep Learning: A Survey.

[BibT_eX]

[DOI]

IEEE Access, 2020

Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning.

[BibT_eX]

[DOI]

Jize Zhang

Karthikeyan Natesan Ramamurthy

Thomas Yong-Jin Han

Proceedings of the 37th International Conference on Machine Learning, 2020

Adversarial Mutual Information for Text Generation.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Towards an Efficient and General Framework of Robust Training for Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Treeview and Disentangled Representations for Explaining Deep Neural Networks Decisions.

[BibT_eX]

[DOI]

Prasanna Sattigeri

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Secure Distributed Detection of Sparse Signals via Falsification of Local Compressive Measurements.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2019

Joint Sparsity Pattern Recovery With 1-b Compressive Sensing in Distributed Sensor Networks.

[BibT_eX]

[DOI]

Swatantra Kafle

Vipul Gupta

IEEE Trans. Signal Inf. Process. over Networks, 2019

Merlin: Enabling Machine Learning-Ready HPC Ensembles.

[BibT_eX]

[DOI]

CoRR, 2019

Deep Probabilistic Kernels for Sample-Efficient Learning.

[BibT_eX]

[DOI]

CoRR, 2019

A Look at the Effect of Sample Design on Generalization through the Lens of Spectral Analysis.

[BibT_eX]

[DOI]

Qunwei Li

CoRR, 2019

On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Generative Counterfactual Introspection for Explainable Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE Global Conference on Signal and Information Processing, 2019

2018

A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms.

[BibT_eX]

[DOI]

Charvi Rastogi

J. Mach. Learn. Res., 2018

MR-GAN: Manifold Regularized Generative Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2018

MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense.

[BibT_eX]

[DOI]

Timo Bremer

CoRR, 2018

Universal Decision-Based Black-Box Perturbations: Breaking Security-Through-Obscurity Defenses.

[BibT_eX]

[DOI]

Thomas A. Hogan

CoRR, 2018

Controlled Random Search Improves Sample Mining and Hyper-Parameter Optimization.

[BibT_eX]

[DOI]

Gowtham Muniraju

CoRR, 2018

An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks.

[BibT_eX]

[DOI]

Timo Bremer

CoRR, 2018

Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

PADDLE: Performance Analysis Using a Data-Driven Learning Environment.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

Human-Machine Inference Networks for Smart Decision Making: Opportunities and Challenges.

[BibT_eX]

[DOI]

Aditya Vempaty

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Secure Networked Inference with Unreliable Data Sources

[BibT_eX]

[DOI]

Aditya Vempaty

Springer, ISBN: 978-981-13-2311-9, 2018

2017

Subspace-Aware Index Codes.

[BibT_eX]

[DOI]

Lakshmi Narasimhan Theagarajan

IEEE Wirel. Commun. Lett., 2017

Collaborative Compressive Detection With Physical Layer Secrecy Constraints.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2017

Data Falsification Attacks on Consensus-Based Detection Systems.

[BibT_eX]

[DOI]

IEEE Trans. Signal Inf. Process. over Networks, 2017

Robust Federated Learning Using ADMM in the Presence of Data Falsifying Byzantines.

[BibT_eX]

[DOI]

CoRR, 2017

Performance modeling under resource constraints using deep transfer learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2017

Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

Byzantine-Resilient locally optimum detection using collaborative autonomous networks.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2016

Measurement Matrix Design for Compressed Detection With Secrecy Guarantees.

[BibT_eX]

[DOI]

Sijia Liu

IEEE Wirel. Commun. Lett., 2016

Stair blue noise sampling.

[BibT_eX]

[DOI]

ACM Trans. Graph., 2016

Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach.

[BibT_eX]

[DOI]

Prashant Khanduri

IEEE Signal Process. Lett., 2016

TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning.

[BibT_eX]

[DOI]

Karthikeyan Natesan Ramamurthy

Prasanna Sattigeri

CoRR, 2016

Influential Node Detection in Implicit Social Networks using Multi-task Gaussian Copula Models.

[BibT_eX]

[DOI]

Qunwei Li

Zhenliang Zhang

Proceedings of the NIPS 2016 Time Series Workshop, 2016

Robust Local Scaling Using Conditional Quantiles of Graph Similarities.

[BibT_eX]

[DOI]

Karthikeyan Natesan Ramamurthy

Prasanna Sattigeri

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Theoretical guarantees for poisson disk sampling using pair correlation function.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Decentralized joint sparsity pattern recovery using 1-bit compressive sensing.

[BibT_eX]

[DOI]

Swatantra Kafle

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2015

Distributed Inference in Tree Networks Using Coding Theory.

[BibT_eX]

[DOI]

Aditya Vempaty

IEEE Trans. Signal Process., 2015

Distributed Bayesian Detection in the Presence of Byzantine Data.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2015

Asymptotic Analysis of Distributed Bayesian Detection with Byzantine Data.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2015

Measurement Matrix Design for Compressive Detection with Secrecy Guarantees.

[BibT_eX]

[DOI]

Sijia Liu

CoRR, 2015

Consensus based Detection in the Presence of Data Falsification Attacks.

[BibT_eX]

[DOI]

CoRR, 2015

Joint Sparsity Pattern Recovery with 1-bit Compressive Sensing in Sensor Networks.

[BibT_eX]

[DOI]

Vipul Gupta

CoRR, 2015

Distributed inference in the presence of eavesdroppers: a survey.

[BibT_eX]

[DOI]

V. Sriram Siddhardh Nadendla

IEEE Commun. Mag., 2015

Joint sparsity pattern recovery with 1-bit compressive sensing in sensor networks.

[BibT_eX]

[DOI]

Vipul Gupta

Sijia Liu

Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015

2014

Distributed Detection in Tree Topologies With Byzantines.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2014

Distributed Detection in Tree Networks: Byzantines and Mitigation Techniques.

[BibT_eX]

[DOI]

CoRR, 2014

Distributed Compressive Detection with Perfect Secrecy.

[BibT_eX]

[DOI]

Lixin Shen

Proceedings of the 11th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, 2014

On the performance analysis of data fusion schemes with Byzantines.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2014

On physical layer secrecy of collaborative compressive detection.

[BibT_eX]

[DOI]

Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2013

Distributed Bayesian Detection with Byzantine Data.

[BibT_eX]

[DOI]

CoRR, 2013

Optimal Byzantine attacks on distributed detection in tree-based topologies.

[BibT_eX]

[DOI]