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05/31/2023
Representer Point Selection for Explaining Regularized High-dimensional Models
We introduce a novel class of sample-based explanations we term high-dim...
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05/31/2023
Red Teaming Language Model Detectors with Language Models
The prevalence and high capacity of large language models (LLMs) present...
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05/30/2023
Universality and Limitations of Prompt Tuning
Despite the demonstrated empirical efficacy of prompt tuning to adapt a ...
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05/29/2023
Robust Lipschitz Bandits to Adversarial Corruptions
Lipschitz bandit is a variant of stochastic bandits that deals with a co...
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05/21/2023
PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation
The eXtreme Multi-label Classification (XMC) problem seeks to find relev...
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04/26/2023
Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories
In this paper, we define, evaluate, and improve the “relay-generalizatio...
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02/18/2023
Online Continuous Hyperparameter Optimization for Contextual Bandits
In stochastic contextual bandit problems, an agent sequentially makes ac...
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02/13/2023
Symbolic Discovery of Optimization Algorithms
We present a method to formulate algorithm discovery as program search, ...
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02/02/2023
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data
“Effective robustness” measures the extra out-of-distribution (OOD) robu...
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11/19/2022
Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory
Dataset distillation methods aim to compress a large dataset into a smal...
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11/07/2022
Are AlphaZero-like Agents Robust to Adversarial Perturbations?
The success of AlphaZero (AZ) has demonstrated that neural-network-based...
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11/04/2022
Improving Adversarial Robustness to Sensitivity and Invariance Attacks with Deep Metric Learning
Intentionally crafted adversarial samples have effectively exploited wea...
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11/01/2022
Preserving In-Context Learning ability in Large Language Model Fine-tuning
Pretrained large language models (LLMs) are strong in-context learners t...
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10/22/2022
ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation
Adversarial Examples Detection (AED) is a crucial defense technique agai...
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10/21/2022
Reducing Training Sample Memorization in GANs by Training with Memorization Rejection
Generative adversarial network (GAN) continues to be a popular research ...
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10/18/2022
Uncertainty in Extreme Multi-label Classification
Uncertainty quantification is one of the most crucial tasks to obtain tr...
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10/16/2022
End-to-End Learning to Index and Search in Large Output Spaces
Extreme multi-label classification (XMC) is a popular framework for solv...
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10/14/2022
Watermarking Pre-trained Language Models with Backdooring
Large pre-trained language models (PLMs) have proven to be a crucial com...
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10/13/2022
Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation
Lipschitz constants are connected to many properties of neural networks,...
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09/27/2022
Efficient Non-Parametric Optimizer Search for Diverse Tasks
Efficient and automated design of optimizers plays a crucial role in ful...
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08/31/2022
Concept Gradient: Concept-based Interpretation Without Linear Assumption
Concept-based interpretations of black-box models are often more intuiti...
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08/11/2022
General Cutting Planes for Bound-Propagation-Based Neural Network Verification
Bound propagation methods, when combined with branch and bound, are amon...
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07/20/2022
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning
Federated learning (FL) has recently attracted increasing attention from...
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07/20/2022
DC-BENCH: Dataset Condensation Benchmark
Dataset Condensation is a newly emerging technique aiming at learning a ...
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06/11/2022
Improving the Adversarial Robustness of NLP Models by Information Bottleneck
Existing studies have demonstrated that adversarial examples can be dire...
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03/29/2022
Generalizing Few-Shot NAS with Gradient Matching
Efficient performance estimation of architectures drawn from large searc...
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03/16/2022
On the Convergence of Certified Robust Training with Interval Bound Propagation
Interval Bound Propagation (IBP) is so far the base of state-of-the-art ...
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03/05/2022
Towards Efficient and Scalable Sharpness-Aware Minimization
Recently, Sharpness-Aware Minimization (SAM), which connects the geometr...
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12/16/2021
Extreme Zero-Shot Learning for Extreme Text Classification
The eXtreme Multi-label text Classification (XMC) problem concerns findi...
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12/15/2021
Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks
Recently, video-based action recognition methods using convolutional neu...
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11/18/2021
A Review of Adversarial Attack and Defense for Classification Methods
Despite the efficiency and scalability of machine learning systems, rece...
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11/02/2021
Can Vision Transformers Perform Convolution?
Several recent studies have demonstrated that attention-based networks, ...
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10/29/2021
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction
Learning on graphs has attracted significant attention in the learning c...
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10/22/2021
How and When Adversarial Robustness Transfers in Knowledge Distillation?
Knowledge distillation (KD) has been widely used in teacher-student trai...
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10/13/2021
Adversarial Attack across Datasets
It has been observed that Deep Neural Networks (DNNs) are vulnerable to ...
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09/05/2021
Training Meta-Surrogate Model for Transferable Adversarial Attack
We consider adversarial attacks to a black-box model when no queries are...
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08/29/2021
Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution
Recent studies have shown that deep neural networks are vulnerable to in...
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08/18/2021
RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving
Predictor-based algorithms have achieved remarkable performance in the N...
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08/17/2021
RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection
3D point cloud understanding has made great progress in recent years. Ho...
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08/10/2021
Rethinking Architecture Selection in Differentiable NAS
Differentiable Neural Architecture Search is one of the most popular Neu...
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06/24/2021
Label Disentanglement in Partition-based Extreme Multilabel Classification
Partition-based methods are increasingly-used in extreme multi-label cla...
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06/05/2021
Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms
The stochastic contextual bandit problem, which models the trade-off bet...
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06/05/2021
Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks
Stochastic linear contextual bandit algorithms have substantial applicat...
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06/03/2021
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification
Attention is sparse in vision transformers. We observe the final predict...
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06/03/2021
When Vision Transformers Outperform ResNets without Pretraining or Strong Data Augmentations
Vision Transformers (ViTs) and MLPs signal further efforts on replacing ...
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06/01/2021
Concurrent Adversarial Learning for Large-Batch Training
Large-batch training has become a commonly used technique when training ...
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05/19/2021
Balancing Robustness and Sensitivity using Feature Contrastive Learning
It is generally believed that robust training of extremely large network...
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05/18/2021
Detecting Adversarial Examples with Bayesian Neural Network
In this paper, we propose a new framework to detect adversarial examples...
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04/30/2021
Deep Image Destruction: A Comprehensive Study on Vulnerability of Deep Image-to-Image Models against Adversarial Attacks
Recently, the vulnerability of deep image classification models to adver...
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04/18/2021