Tom Goldstein

Michael-Andrei Panaitescu-Liess

David Wipf

Trans. Mach. Learn. Res., 2024

Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization.

[BibT_eX]

[DOI]

CoRR, 2024

Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data?

[BibT_eX]

[DOI]

Zora Che

Bang An

Yuancheng Xu

Pankayaraj Pathmanathan

CoRR, 2024

LiveBench: A Challenging, Contamination-Free LLM Benchmark.

[BibT_eX]

[DOI]

CoRR, 2024

From Pixels to Prose: A Large Dataset of Dense Image Captions.

[BibT_eX]

[DOI]

CoRR, 2024

GenQA: Generating Millions of Instructions from a Handful of Prompts.

[BibT_eX]

[DOI]

CoRR, 2024

PUP 3D-GS: Principled Uncertainty Pruning for 3D Gaussian Splatting.

[BibT_eX]

[DOI]

CoRR, 2024

Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs.

[BibT_eX]

[DOI]

CoRR, 2024

OPTune: Efficient Online Preference Tuning.

[BibT_eX]

[DOI]

CoRR, 2024

The CLRS-Text Algorithmic Reasoning Language Benchmark.

[BibT_eX]

[DOI]

CoRR, 2024

Transformers Can Do Arithmetic with the Right Embeddings.

[BibT_eX]

[DOI]

CoRR, 2024

Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement.

[BibT_eX]

[DOI]

CoRR, 2024

CinePile: A Long Video Question Answering Dataset and Benchmark.

[BibT_eX]

[DOI]

CoRR, 2024

LMD3: Language Model Data Density Dependence.

[BibT_eX]

[DOI]

CoRR, 2024

Benchmarking ChatGPT on Algorithmic Reasoning.

[BibT_eX]

[DOI]

Sean McLeish

Avi Schwarzschild

CoRR, 2024

Measuring Style Similarity in Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2024

Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models.

[BibT_eX]

[DOI]

CoRR, 2024

Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion.

[BibT_eX]

[DOI]

CoRR, 2024

What do we learn from inverting CLIP models?

[BibT_eX]

[DOI]

Hamid Kazemi

Atoosa Malemir Chegini

Soheil Feizi

CoRR, 2024

Coercing LLMs to do and reveal (almost) anything.

[BibT_eX]

[DOI]

CoRR, 2024

Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

Benchmarking the Robustness of Image Watermarks.

[BibT_eX]

[DOI]

CoRR, 2024

Hierarchical Point Attention for Indoor 3D Object Detection.

[BibT_eX]

[DOI]

Manli Shu

Le Xue

Ning Yu

Roberto Martín-Martín

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text.

[BibT_eX]

[DOI]

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

InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models.

[BibT_eX]

[DOI]

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

ODIN: Disentangled Reward Mitigates Hacking in RLHF.

[BibT_eX]

[DOI]

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

WAVES: Benchmarking the Robustness of Image Watermarks.

[BibT_eX]

[DOI]

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

On the Reliability of Watermarks for Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

NEFTune: Noisy Embeddings Improve Instruction Finetuning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

FedAQT: Accurate Quantized Training with Federated Learning.

[BibT_eX]

[DOI]

Ananda Theertha Suresh

Ignacio López-Moreno

Mingqing Chen

Rajiv Mathews

Proceedings of the IEEE International Conference on Acoustics, 2024

Object Recognition as Next Token Prediction.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Towards Transferable Adversarial Attacks on Image and Video Transformers.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2023

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Universal Pyramid Adversarial Training for Improved ViT Performance.

[BibT_eX]

[DOI]

CoRR, 2023

Perspectives on the State and Future of Deep Learning - 2023.

[BibT_eX]

[DOI]

CoRR, 2023

A Simple and Efficient Baseline for Data Attribution on Images.

[BibT_eX]

[DOI]

Vasu Singla

Micah Goldblum

CoRR, 2023

Baseline Defenses for Adversarial Attacks Against Aligned Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

Bring Your Own Data! Self-Supervised Evaluation for Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust.

[BibT_eX]

[DOI]

CoRR, 2023

A Cookbook of Self-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2023

JPEG Compressed Images Can Bypass Protections Against AI Editing.

[BibT_eX]

[DOI]

CoRR, 2023

Neural Auctions Compromise Bidder Information.

[BibT_eX]

[DOI]

CoRR, 2023

Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images.

[BibT_eX]

[DOI]

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

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery.

[BibT_eX]

[DOI]

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

Understanding and Mitigating Copying in Diffusion Models.

[BibT_eX]

[DOI]

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

On the Exploitability of Instruction Tuning.

[BibT_eX]

[DOI]

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

What Can We Learn from Unlearnable Datasets?

[BibT_eX]

[DOI]

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

Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks.

[BibT_eX]

[DOI]

Prithvijit Chattopadhyay

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

A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning.

[BibT_eX]

[DOI]

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

Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise.

[BibT_eX]

[DOI]

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

GOAT: A Global Transformer on Large-scale Graphs.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

A Watermark for Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Cramming: Training a Language Model on a single GPU in one day.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Seeing in Words: Learning to Classify through Language Bottlenecks.

[BibT_eX]

[DOI]

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Transfer Learning with Deep Tabular Models.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Provable Robustness against Wasserstein Distribution Shifts via Input Randomization.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

STYX: Adaptive Poisoning Attacks Against Byzantine-Robust Defenses in Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Universal Guidance for Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Unifying the Harmonic Analysis of Adversarial Attacks and Robustness.

[BibT_eX]

[DOI]

Proceedings of the 34th British Machine Vision Conference 2023, 2023

A Deep Dive into Dataset Imbalance and Bias in Face Identification.

[BibT_eX]

[DOI]

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

Joint Channel Estimation and Data Detection in Cell-Free Massive MU-MIMO Systems.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2022

What do Vision Transformers Learn? A Visual Exploration.

[BibT_eX]

[DOI]

CoRR, 2022

K-SAM: Sharpness-Aware Minimization at the Speed of SGD.

[BibT_eX]

[DOI]

CoRR, 2022

Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise.

[BibT_eX]

[DOI]

CoRR, 2022

A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features.

[BibT_eX]

[DOI]

David Wipf

CoRR, 2022

A Deep Dive into Dataset Imbalance and Bias in Face Identification.

[BibT_eX]

[DOI]

CoRR, 2022

End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking.

[BibT_eX]

[DOI]

CoRR, 2022

Certifying Model Accuracy under Distribution Shifts.

[BibT_eX]

[DOI]

CoRR, 2022

Execute Order 66: Targeted Data Poisoning for Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch.

[BibT_eX]

[DOI]

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

Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models.

[BibT_eX]

[DOI]

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

Autoregressive Perturbations for Data Poisoning.

[BibT_eX]

[DOI]

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

Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability.

[BibT_eX]

[DOI]

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

Robustness Disparities in Face Detection.

[BibT_eX]

[DOI]

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

End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking.

[BibT_eX]

[DOI]

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

Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Certified Neural Network Watermarks with Randomized Smoothing.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

The Uncanny Similarity of Recurrence and Depth.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

The Close Relationship Between Contrastive Learning and Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Stochastic Training is Not Necessary for Generalization.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Poisons that are learned faster are more effective.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Robust Optimization as Data Augmentation for Large-scale Graphs.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Learning Revenue-Maximizing Auctions With Differentiable Matching.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Towards Transferable Adversarial Attacks on Vision Transformers.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Active Learning at the ImageNet Scale.

[BibT_eX]

[DOI]

CoRR, 2021

A Frequency Perspective of Adversarial Robustness.

[BibT_eX]

[DOI]

CoRR, 2021

Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features.

[BibT_eX]

[DOI]

CoRR, 2021

Comparing Human and Machine Bias in Face Recognition.

[BibT_eX]

[DOI]

Gudrun Thorkelsdottir

CoRR, 2021

Robustness Disparities in Commercial Face Detection.

[BibT_eX]

[DOI]

Samuel Dooley

John P. Dickerson

CoRR, 2021

Datasets for Studying Generalization from Easy to Hard Examples.

[BibT_eX]

[DOI]

CoRR, 2021

MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data.

[BibT_eX]

[DOI]

CoRR, 2021

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training.

[BibT_eX]

[DOI]

CoRR, 2021

THAT: Two Head Adversarial Training for Improving Robustness at Scale.

[BibT_eX]

[DOI]

CoRR, 2021

Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving.

[BibT_eX]

[DOI]

CoRR, 2021

Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release.

[BibT_eX]

[DOI]

CoRR, 2021

DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations.

[BibT_eX]

[DOI]

CoRR, 2021

What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors.

[BibT_eX]

[DOI]

CoRR, 2021

Improving Robustness of Learning-based Autonomous Steering Using Adversarial Images.

[BibT_eX]

[DOI]

CoRR, 2021

Thinking Deeply with Recurrence: Generalizing from Easy to Hard Sequential Reasoning Problems.

[BibT_eX]

[DOI]

CoRR, 2021

Center Smoothing for Certifiably Robust Vector-Valued Functions.

[BibT_eX]

[DOI]

Aounon Kumar

CoRR, 2021

Technical Challenges for Training Fair Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2021

MaxVA: Fast Adaptation of Step Sizes by Maximizing Observed Variance of Gradients.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Long-Short Transformer: Efficient Transformers for Language and Vision.

[BibT_eX]

[DOI]

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

GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training.

[BibT_eX]

[DOI]

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

Encoding Robustness to Image Style via Adversarial Feature Perturbations.

[BibT_eX]

[DOI]

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

Gradient-Free Adversarial Training Against Image Corruption for Learning-based Steering.

[BibT_eX]

[DOI]

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

Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks.

[BibT_eX]

[DOI]

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

Center Smoothing: Certified Robustness for Networks with Structured Outputs.

[BibT_eX]

[DOI]

Aounon Kumar

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

Adversarial Examples Make Strong Poisons.

[BibT_eX]

[DOI]

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

VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization.

[BibT_eX]

[DOI]

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

Adversarial Differentiable Data Augmentation for Autonomous Systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Data Augmentation for Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

The Intrinsic Dimension of Images and Its Impact on Learning.

[BibT_eX]

[DOI]

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

WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic.

[BibT_eX]

[DOI]

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

Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching.

[BibT_eX]

[DOI]

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

LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition.

[BibT_eX]

[DOI]

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

Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

Adversarial attacks on machine learning systems for high-frequency trading.

[BibT_eX]

[DOI]

Proceedings of the ICAIF'21: 2nd ACM International Conference on AI in Finance, Virtual Event, November 3, 2021

Hybrid Jammer Mitigation for All-Digital mmWave Massive MU-MIMO.

[BibT_eX]

[DOI]

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks.

[BibT_eX]

[DOI]

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

2020

High-Bandwidth Spatial Equalization for mmWave Massive MU-MIMO With Processing-in-Memory.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. II Express Briefs, 2020

Finite-Alphabet MMSE Equalization for All-Digital Massive MU-MIMO mmWave Communication.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2020

Analyzing the Machine Learning Conference Review Process.

[BibT_eX]

[DOI]

CoRR, 2020

Tight Second-Order Certificates for Randomized Smoothing.

[BibT_eX]

[DOI]

CoRR, 2020

FLAG: Adversarial Data Augmentation for Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer.

[BibT_eX]

[DOI]

CoRR, 2020

Random Network Distillation as a Diversity Metric for Both Image and Text Generation.

[BibT_eX]

[DOI]

CoRR, 2020

ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2020

An Open Review of OpenReview: A Critical Analysis of the Machine Learning Conference Review Process.

[BibT_eX]

[DOI]

CoRR, 2020

Prepare for the Worst: Generalizing across Domain Shifts with Adversarial Batch Normalization.

[BibT_eX]

[DOI]

CoRR, 2020

WrapNet: Neural Net Inference with Ultra-Low-Resolution Arithmetic.

[BibT_eX]

[DOI]

CoRR, 2020

Detection as Regression: Certified Object Detection by Median Smoothing.

[BibT_eX]

[DOI]

CoRR, 2020

Adaptive Learning Rates with Maximum Variation Averaging.

[BibT_eX]

[DOI]

CoRR, 2020

Exploring Model Robustness with Adaptive Networks and Improved Adversarial Training.

[BibT_eX]

[DOI]

Ali Shafahi

CoRR, 2020

Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers.

[BibT_eX]

[DOI]

CoRR, 2020

Adversarial Attacks on Machine Learning Systems for High-Frequency Trading.

[BibT_eX]

[DOI]

CoRR, 2020

Certifying Confidence via Randomized Smoothing.

[BibT_eX]

[DOI]

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

MetaPoison: Practical General-purpose Clean-label Data Poisoning.

[BibT_eX]

[DOI]

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

Adversarially Robust Few-Shot Learning: A Meta-Learning Approach.

[BibT_eX]

[DOI]

Micah Goldblum

Liam Fowl

Karthik Abinav Sankararaman

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

Certifying Strategyproof Auction Networks.

[BibT_eX]

[DOI]

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

Detection as Regression: Certified Object Detection with Median Smoothing.

[BibT_eX]

[DOI]

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

The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent.

[BibT_eX]

[DOI]

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

Adversarial Attacks on Copyright Detection Systems.

[BibT_eX]

[DOI]

Parsa Saadatpanah

Ali Shafahi

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

Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness.

[BibT_eX]

[DOI]

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

Certified Data Removal from Machine Learning Models.

[BibT_eX]

[DOI]

Chuan Guo

Awni Y. Hannun

Laurens van der Maaten

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

Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks.

[BibT_eX]

[DOI]

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

FreeLB: Enhanced Adversarial Training for Natural Language Understanding.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Network Deconvolution.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Adversarially robust transfer learning.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Truth or backpropaganda? An empirical investigation of deep learning theory.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Breaking Certified Defenses: Semantic Adversarial Examples with Spoofed robustness Certificates.

[BibT_eX]

[DOI]

Amin Ghiasi

Ali Shafahi

Proceedings of the 8th International Conference on Learning Representations, 2020

Certified Defenses for Adversarial Patches.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Understanding Generalization Through Visualizations.

[BibT_eX]

[DOI]

Proceedings of the "I Can't Believe It's Not Better!" at NeurIPS Workshops, 2020

Witchcraft: Efficient PGD Attacks with Random Step Size.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Soft-Output Finite Alphabet Equalization for mmWave Massive MIMO.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Headless Horseman: Adversarial Attacks on Transfer Learning Models.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Deep k-NN Defense Against Clean-Label Data Poisoning Attacks.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

MSE-Optimal Neural Network Initialization via Layer Fusion.

[BibT_eX]

[DOI]

Proceedings of the 54th Annual Conference on Information Sciences and Systems, 2020

Making L-BFGS Work with Industrial-Strength Nets.

[BibT_eX]

[DOI]

Abhay Kumar Yadav

David W. Jacobs

Proceedings of the 31st British Machine Vision Conference 2020, 2020

Hardware-Friendly Two-Stage Spatial Equalization for All-Digital mmWave Massive MU-MIMO.

[BibT_eX]

[DOI]

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

Universal Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Adversarially Robust Distillation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training?

[BibT_eX]

[DOI]

CoRR, 2019

Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets.

[BibT_eX]

[DOI]

Yogesh Balaji

Judy Hoffman

CoRR, 2019

Robust Few-Shot Learning with Adversarially Queried Meta-Learners.

[BibT_eX]

[DOI]

Micah Goldblum

Liam Fowl

CoRR, 2019

Strong Baseline Defenses Against Clean-Label Poisoning Attacks.

[BibT_eX]

[DOI]

CoRR, 2019

FreeLB: Enhanced Adversarial Training for Language Understanding.

[BibT_eX]

[DOI]

CoRR, 2019

Transferable Clean-Label Poisoning Attacks on Deep Neural Nets.

[BibT_eX]

[DOI]

CoRR, 2019

Understanding the (un)interpretability of natural image distributions using generative models.

[BibT_eX]

[DOI]

CoRR, 2019

Improving Channel Charting with Representation -Constrained Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2019

Adversarial training for free!

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Transferable Clean-Label Poisoning Attacks on Deep Neural Nets.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Are adversarial examples inevitable?

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

ACE: Adapting to Changing Environments for Semantic Segmentation.

[BibT_eX]

[DOI]

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

Batch-wise Logit-Similarity: Generalizing Logit-Squeezing and Label-Smoothing.

[BibT_eX]

[DOI]

Proceedings of the 30th British Machine Vision Conference 2019, 2019

Siamese Neural Networks for Wireless Positioning and Channel Charting.

[BibT_eX]

[DOI]

Proceedings of the 57th Annual Allerton Conference on Communication, 2019

Finite-Alphabet Wiener Filter Precoding for mmWave Massive MU-MIMO Systems.

[BibT_eX]

[DOI]

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

PhaseMax: Convex Phase Retrieval via Basis Pursuit.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2018

VLSI Designs for Joint Channel Estimation and Data Detection in Large SIMO Wireless Systems.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. I Regul. Pap., 2018

Solving Uncalibrated Photometric Stereo Using Fewer Images by Jointly Optimizing Low-rank Matrix Completion and Integrability.

[BibT_eX]

[DOI]

J. Math. Imaging Vis., 2018

Stacked U-Nets: A No-Frills Approach to Natural Image Segmentation.

[BibT_eX]

[DOI]

CoRR, 2018

Channel Charting: Locating Users Within the Radio Environment Using Channel State Information.

[BibT_eX]

[DOI]

IEEE Access, 2018

Challenges for Machine Learning on Distributed Platforms (Invited Talk).

[BibT_eX]

[DOI]

Proceedings of the 32nd International Symposium on Distributed Computing, 2018

Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks.

[BibT_eX]

[DOI]

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

Visualizing the Loss Landscape of Neural Nets.

[BibT_eX]

[DOI]

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

VLSI Design of a 3-bit Constant-Modulus Precoder for Massive MU-MIMO.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Circuits and Systems, 2018

Linear Spectral Estimators and an Application to Phase Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Stabilizing Adversarial Nets with Prediction Methods.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Unsupervised Charting of Wireless Channels.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2018

DCAN: Dual Channel-Wise Alignment Networks for Unsupervised Scene Adaptation.

[BibT_eX]

[DOI]

Zuxuan Wu

Xintong Han

Yen-Liang Lin

Mustafa Gökhan Uzunbas

Aswin C. Sankaranarayanan

Ser-Nam Lim

Larry S. Davis

Proceedings of the Computer Vision - ECCV 2018, 2018

PhaseLin: Linear phase retrieval.

[BibT_eX]

[DOI]

Proceedings of the 52nd Annual Conference on Information Sciences and Systems, 2018

2017

Quantized Precoding for Massive MU-MIMO.

[BibT_eX]

[DOI]

IEEE Trans. Commun., 2017

Compressive Video Sensing: Algorithms, architectures, and applications.

[BibT_eX]

[DOI]

Richard G. Baraniuk

Thomas A. Goldstein

Ashok Veeraraghavan

Michael B. Wakin

IEEE Signal Process. Mag., 2017

Decentralized Baseband Processing for Massive MU-MIMO Systems.

[BibT_eX]

[DOI]

IEEE J. Emerg. Sel. Topics Circuits Syst., 2017

1-bit Massive MU-MIMO Precoding in VLSI.

[BibT_eX]

[DOI]

IEEE J. Emerg. Sel. Topics Circuits Syst., 2017

Visualizing the Loss Landscape of Neural Nets.

[BibT_eX]

[DOI]

CoRR, 2017

PhasePack User Guide.

[BibT_eX]

[DOI]

CoRR, 2017

Training Quantized Nets: A Deeper Understanding.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

FPGA design of low-complexity joint channel estimation and data detection for large SIMO wireless systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Circuits and Systems, 2017

Convex Phase Retrieval without Lifting via PhaseMax.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

Adaptive Consensus ADMM for Distributed Optimization.

[BibT_eX]

[DOI]

Hao Li

Xiaoming Yuan

Proceedings of the 34th International Conference on Machine Learning, 2017

Son of Zorn's lemma: Targeted style transfer using instance-aware semantic segmentation.

[BibT_eX]

[DOI]

Carlos Domingo Castillo

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

POKEMON: A non-linear beamforming algorithm for 1-bit massive MIMO.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

A New Rank Constraint on Multi-view Fundamental Matrices, and Its Application to Camera Location Recovery.

[BibT_eX]

[DOI]

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

Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation.

[BibT_eX]

[DOI]

Xiaoming Yuan

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

Automated Inference with Adaptive Batches.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Adaptive ADMM with Spectral Penalty Parameter Selection.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

PhasePack: A phase retrieval library.

[BibT_eX]

[DOI]

Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

Scalable Classifiers with ADMM and Transpose Reduction.

[BibT_eX]

[DOI]

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Data Detection in Large Multi-Antenna Wireless Systems via Approximate Semidefinite Relaxation.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. I Regul. Pap., 2016

Biconvex Relaxation for Semidefinite Programming in Computer Vision.

[BibT_eX]

[DOI]

CoRR, 2016

Big Batch SGD: Automated Inference using Adaptive Batch Sizes.

[BibT_eX]

[DOI]

CoRR, 2016

Non-negative Factorization of the Occurrence Tensor from Financial Contracts.

[BibT_eX]

[DOI]

CoRR, 2016

An Empirical Study of ADMM for Nonconvex Problems.

[BibT_eX]

[DOI]

CoRR, 2016

Deterministic Column Sampling for Low-Rank Matrix Approximation: Nyström vs. Incomplete Cholesky Decomposition.

[BibT_eX]

[DOI]

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

FPGA design of approximate semidefinite relaxation for data detection in large MIMO wireless systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

Training Neural Networks Without Gradients: A Scalable ADMM Approach.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Dealbreaker: A Nonlinear Latent Variable Model for Educational Data.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Efficient Distributed SGD with Variance Reduction.

[BibT_eX]

[DOI]

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Decentralized beamforming for massive MU-MIMO on a GPU cluster.

[BibT_eX]

[DOI]

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

Biconvex Relaxation for Semidefinite Programming in Computer Vision.

[BibT_eX]

[DOI]

Sohil Shah

Abhay Kumar Yadav

Carlos Domingo Castillo

David W. Jacobs

Proceedings of the Computer Vision - ECCV 2016, 2016

ShapeFit and ShapeKick for Robust, Scalable Structure from Motion.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2016, 2016

Estimating Sparse Signals with Smooth Support via Convex Programming and Block Sparsity.

[BibT_eX]

[DOI]

Sohil Shah

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Decentralized data detection for massive MU-MIMO on a Xeon Phi cluster.

[BibT_eX]

[DOI]

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

Nonlinear 1-bit precoding for massive MU-MIMO with higher-order modulation.

[BibT_eX]

[DOI]

Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015

The STOne Transform: Multi-Resolution Image Enhancement and Compressive Video.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2015

oASIS: Adaptive Column Sampling for Kernel Matrix Approximation.

[BibT_eX]

[DOI]

CoRR, 2015

FASTA: A Generalized Implementation of Forward-Backward Splitting.

[BibT_eX]

[DOI]

Richard G. Baraniuk

CoRR, 2015

Self-Expressive Decompositions for Matrix Approximation and Clustering.

[BibT_eX]

[DOI]

CoRR, 2015

Scaling Up Distributed Stochastic Gradient Descent Using Variance Reduction.

[BibT_eX]

[DOI]

CoRR, 2015

Variance Reduction for Distributed Stochastic Gradient Descent.

[BibT_eX]

[DOI]

CoRR, 2015

Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing.

[BibT_eX]

[DOI]

Min Li

Xiaoming Yuan

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Layer-Specific Adaptive Learning Rates for Deep Networks.

[BibT_eX]

[DOI]

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

Exploiting Low-rank Structure for Discriminative Sub-categorization.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference 2015, 2015

2014

Fast Alternating Direction Optimization Methods.

[BibT_eX]

[DOI]

SIAM J. Imaging Sci., 2014

Democratic Representations.

[BibT_eX]

[DOI]

CoRR, 2014

A Field Guide to Forward-Backward Splitting with a FASTA Implementation.

[BibT_eX]

[DOI]

Richard G. Baraniuk

CoRR, 2014

Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit.

[BibT_eX]

[DOI]

CoRR, 2014

2013

The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive Video.

[BibT_eX]

[DOI]

CoRR, 2013

Adaptive step size selection for optimization via the ski rental problem.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2013

2010

Geometric Applications of the Split Bregman Method: Segmentation and Surface Reconstruction.

[BibT_eX]

[DOI]

Xavier Bresson

Stanley J. Osher

J. Sci. Comput., 2010

2009

The Split Bregman Method for L1-Regularized Problems.

[BibT_eX]

[DOI]

Stanley J. Osher

SIAM J. Imaging Sci., 2009

2004

Perceptual speech quality assessment in acoustic and binaural applications.

[BibT_eX]

[DOI]