Timezone: »
Spotlight
Learning to Generate Noise for Multi-Attack Robustness
Divyam Madaan · Jinwoo Shin · Sung Ju Hwang
Adversarial learning has emerged as one of the successful techniques to circumvent the susceptibility of existing methods against adversarial perturbations. However, the majority of existing defense methods are tailored to defend against a single category of adversarial perturbation (e.g. $\ell_\infty$-attack). In safety-critical applications, this makes these methods extraneous as the attacker can adopt diverse adversaries to deceive the system. Moreover, training on multiple perturbations simultaneously significantly increases the computational overhead during training. To address these challenges, we propose a novel meta-learning framework that explicitly learns to generate noise to improve the model's robustness against multiple types of attacks. Its key component is \emph{Meta Noise Generator (MNG)} that outputs optimal noise to stochastically perturb a given sample, such that it helps lower the error on diverse adversarial perturbations. By utilizing samples generated by MNG, we train a model by enforcing the label consistency across multiple perturbations. We validate the robustness of models trained by our scheme on various datasets and against a wide variety of perturbations, demonstrating that it significantly outperforms the baselines across multiple perturbations with a marginal computational cost.
Author Information
Divyam Madaan (KAIST)
Jinwoo Shin (KAIST)
Sung Ju Hwang (KAIST, AITRICS)
Related Events (a corresponding poster, oral, or spotlight)
-
2021 Poster: Learning to Generate Noise for Multi-Attack Robustness »
Thu. Jul 22nd 04:00 -- 06:00 PM Room Virtual
More from the Same Authors
-
2021 : SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Adversarial Robustness »
Jongheon Jeong · Sejun Park · Minkyu Kim · Heung-Chang Lee · Doguk Kim · Jinwoo Shin -
2021 : Entropy Weighted Adversarial Training »
Minseon Kim · Jihoon Tack · Jinwoo Shin · Sung Ju Hwang -
2021 : Consistency Regularization for Adversarial Robustness »
Jihoon Tack · Sihyun Yu · Jongheon Jeong · Minseon Kim · Sung Ju Hwang · Jinwoo Shin -
2023 : Few-shot Anomaly Detection via Personalization »
Sangkyung Kwak · Jongheon Jeong · Hankook Lee · Woohyuck Kim · Jinwoo Shin -
2023 : Bias-to-Text: Debiasing Unknown Visual Biases by Language Interpretation »
Younghyun Kim · Sangwoo Mo · Minkyu Kim · Kyungmin Lee · Jaeho Lee · Jinwoo Shin -
2023 : Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling »
Jun Hyun Nam · Sangwoo Mo · Jaeho Lee · Jinwoo Shin -
2023 : Guide Your Agent with Adaptive Multimodal Rewards »
Changyeon Kim · Younggyo Seo · Hao Liu · Lisa Lee · Jinwoo Shin · Honglak Lee · Kimin Lee -
2023 : Collaborative Score Distillation for Consistent Visual Synthesis »
Subin Kim · Kyungmin Lee · June Suk Choi · Jongheon Jeong · Kihyuk Sohn · Jinwoo Shin -
2023 : Semi-supervised Tabular Classification via In-context Learning of Large Language Models »
Jaehyun Nam · Woomin Song · Seong Hyeon Park · Jihoon Tack · Sukmin Yun · Jaehyung Kim · Jinwoo Shin -
2023 : Towards Safe Self-Distillation of Internet-Scale Text-to-Image Diffusion Models »
Sanghyun Kim · Seohyeon Jung · Balhae Kim · Moonseok Choi · Jinwoo Shin · Juho Lee -
2023 Poster: Prefer to Classify: Improving Text Classifiers via Auxiliary Preference Learning »
Jaehyung Kim · Jinwoo Shin · Dongyeop Kang -
2023 Poster: Modality-Agnostic Variational Compression of Implicit Neural Representations »
Jonathan Richard Schwarz · Jihoon Tack · Yee-Whye Teh · Jaeho Lee · Jinwoo Shin -
2023 Poster: Multi-View Masked World Models for Visual Robotic Manipulation »
Younggyo Seo · Junsu Kim · Stephen James · Kimin Lee · Jinwoo Shin · Pieter Abbeel -
2022 Poster: TSPipe: Learn from Teacher Faster with Pipelines »
Hwijoon Lim · Yechan Kim · Sukmin Yun · Jinwoo Shin · Dongsu Han -
2022 Poster: Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations »
Jaehyeong Jo · Seul Lee · Sung Ju Hwang -
2022 Spotlight: Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations »
Jaehyeong Jo · Seul Lee · Sung Ju Hwang -
2022 Spotlight: TSPipe: Learn from Teacher Faster with Pipelines »
Hwijoon Lim · Yechan Kim · Sukmin Yun · Jinwoo Shin · Dongsu Han -
2022 Poster: Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning »
Kyunghwan Son · Junsu Kim · Sungsoo Ahn · Roben Delos Reyes · Yung Yi · Jinwoo Shin -
2022 Poster: Forget-free Continual Learning with Winning Subnetworks »
Haeyong Kang · Rusty Mina · Sultan Rizky Hikmawan Madjid · Jaehong Yoon · Mark Hasegawa-Johnson · Sung Ju Hwang · Chang Yoo -
2022 Poster: Set Based Stochastic Subsampling »
Bruno Andreis · Seanie Lee · A. Tuan Nguyen · Juho Lee · Eunho Yang · Sung Ju Hwang -
2022 Poster: Time Is MattEr: Temporal Self-supervision for Video Transformers »
Sukmin Yun · Jaehyung Kim · Dongyoon Han · Hwanjun Song · Jung-Woo Ha · Jinwoo Shin -
2022 Poster: Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization »
Jaehong Yoon · Geon Park · Wonyong Jeong · Sung Ju Hwang -
2022 Spotlight: Forget-free Continual Learning with Winning Subnetworks »
Haeyong Kang · Rusty Mina · Sultan Rizky Hikmawan Madjid · Jaehong Yoon · Mark Hasegawa-Johnson · Sung Ju Hwang · Chang Yoo -
2022 Spotlight: Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning »
Kyunghwan Son · Junsu Kim · Sungsoo Ahn · Roben Delos Reyes · Yung Yi · Jinwoo Shin -
2022 Spotlight: Time Is MattEr: Temporal Self-supervision for Video Transformers »
Sukmin Yun · Jaehyung Kim · Dongyoon Han · Hwanjun Song · Jung-Woo Ha · Jinwoo Shin -
2022 Spotlight: Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization »
Jaehong Yoon · Geon Park · Wonyong Jeong · Sung Ju Hwang -
2022 Spotlight: Set Based Stochastic Subsampling »
Bruno Andreis · Seanie Lee · A. Tuan Nguyen · Juho Lee · Eunho Yang · Sung Ju Hwang -
2021 : Contrastive Learning for Novelty Detection »
Jinwoo Shin -
2021 Poster: Large-Scale Meta-Learning with Continual Trajectory Shifting »
JaeWoong Shin · Hae Beom Lee · Boqing Gong · Sung Ju Hwang -
2021 Poster: Self-Improved Retrosynthetic Planning »
Junsu Kim · Sungsoo Ahn · Hankook Lee · Jinwoo Shin -
2021 Spotlight: Self-Improved Retrosynthetic Planning »
Junsu Kim · Sungsoo Ahn · Hankook Lee · Jinwoo Shin -
2021 Spotlight: Large-Scale Meta-Learning with Continual Trajectory Shifting »
JaeWoong Shin · Hae Beom Lee · Boqing Gong · Sung Ju Hwang -
2021 Poster: Adversarial Purification with Score-based Generative Models »
Jongmin Yoon · Sung Ju Hwang · Juho Lee -
2021 Spotlight: Adversarial Purification with Score-based Generative Models »
Jongmin Yoon · Sung Ju Hwang · Juho Lee -
2021 Poster: Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation »
Dongchan Min · Dong Bok Lee · Eunho Yang · Sung Ju Hwang -
2021 Spotlight: Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation »
Dongchan Min · Dong Bok Lee · Eunho Yang · Sung Ju Hwang -
2021 Poster: Federated Continual Learning with Weighted Inter-client Transfer »
Jaehong Yoon · Wonyong Jeong · GiWoong Lee · Eunho Yang · Sung Ju Hwang -
2021 Poster: State Entropy Maximization with Random Encoders for Efficient Exploration »
Younggyo Seo · Lili Chen · Jinwoo Shin · Honglak Lee · Pieter Abbeel · Kimin Lee -
2021 Spotlight: Federated Continual Learning with Weighted Inter-client Transfer »
Jaehong Yoon · Wonyong Jeong · GiWoong Lee · Eunho Yang · Sung Ju Hwang -
2021 Spotlight: State Entropy Maximization with Random Encoders for Efficient Exploration »
Younggyo Seo · Lili Chen · Jinwoo Shin · Honglak Lee · Pieter Abbeel · Kimin Lee -
2020 Poster: Cost-Effective Interactive Attention Learning with Neural Attention Processes »
Jay Heo · Junhyeon Park · Hyewon Jeong · Kwang Joon Kim · Juho Lee · Eunho Yang · Sung Ju Hwang -
2020 Poster: Meta Variance Transfer: Learning to Augment from the Others »
Seong-Jin Park · Seungju Han · Ji-won Baek · Insoo Kim · Juhwan Song · Hae Beom Lee · Jae-Joon Han · Sung Ju Hwang -
2020 Poster: Self-supervised Label Augmentation via Input Transformations »
Hankook Lee · Sung Ju Hwang · Jinwoo Shin -
2020 Poster: Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning »
Kimin Lee · Younggyo Seo · Seunghyun Lee · Honglak Lee · Jinwoo Shin -
2020 Poster: Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix »
Insu Han · Haim Avron · Jinwoo Shin -
2020 Poster: Learning What to Defer for Maximum Independent Sets »
Sungsoo Ahn · Younggyo Seo · Jinwoo Shin -
2020 Poster: Adversarial Neural Pruning with Latent Vulnerability Suppression »
Divyam Madaan · Jinwoo Shin · Sung Ju Hwang -
2019 Poster: Spectral Approximate Inference »
Sejun Park · Eunho Yang · Se-Young Yun · Jinwoo Shin -
2019 Poster: Robust Inference via Generative Classifiers for Handling Noisy Labels »
Kimin Lee · Sukmin Yun · Kibok Lee · Honglak Lee · Bo Li · Jinwoo Shin -
2019 Poster: Learning What and Where to Transfer »
Yunhun Jang · Hankook Lee · Sung Ju Hwang · Jinwoo Shin -
2019 Oral: Spectral Approximate Inference »
Sejun Park · Eunho Yang · Se-Young Yun · Jinwoo Shin -
2019 Oral: Robust Inference via Generative Classifiers for Handling Noisy Labels »
Kimin Lee · Sukmin Yun · Kibok Lee · Honglak Lee · Bo Li · Jinwoo Shin -
2019 Oral: Learning What and Where to Transfer »
Yunhun Jang · Hankook Lee · Sung Ju Hwang · Jinwoo Shin -
2019 Poster: Training CNNs with Selective Allocation of Channels »
Jongheon Jeong · Jinwoo Shin -
2019 Oral: Training CNNs with Selective Allocation of Channels »
Jongheon Jeong · Jinwoo Shin -
2018 Poster: Deep Asymmetric Multi-task Feature Learning »
Hae Beom Lee · Eunho Yang · Sung Ju Hwang -
2018 Poster: Bucket Renormalization for Approximate Inference »
Sungsoo Ahn · Michael Chertkov · Adrian Weller · Jinwoo Shin -
2018 Oral: Deep Asymmetric Multi-task Feature Learning »
Hae Beom Lee · Eunho Yang · Sung Ju Hwang -
2018 Oral: Bucket Renormalization for Approximate Inference »
Sungsoo Ahn · Michael Chertkov · Adrian Weller · Jinwoo Shin -
2017 Poster: Faster Greedy MAP Inference for Determinantal Point Processes »
Insu Han · Prabhanjan Kambadur · Kyoungsoo Park · Jinwoo Shin -
2017 Poster: Confident Multiple Choice Learning »
Kimin Lee · Changho Hwang · KyoungSoo Park · Jinwoo Shin -
2017 Talk: Confident Multiple Choice Learning »
Kimin Lee · Changho Hwang · KyoungSoo Park · Jinwoo Shin -
2017 Talk: Faster Greedy MAP Inference for Determinantal Point Processes »
Insu Han · Prabhanjan Kambadur · Kyoungsoo Park · Jinwoo Shin