Cho-Jui Hsieh

According to our database1, Cho-Jui Hsieh authored at least 232 papers between 2008 and 2022.

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Bibliography

2022
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning.
CoRR, 2022

DC-BENCH: Dataset Condensation Benchmark.
CoRR, 2022

FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search.
CoRR, 2022

Generalizing Few-Shot NAS with Gradient Matching.
CoRR, 2022

On the Convergence of Certified Robust Training with Interval Bound Propagation.
CoRR, 2022

Towards Efficient and Scalable Sharpness-Aware Minimization.
CoRR, 2022

Relevance under the Iceberg: Reasonable Prediction for Extreme Multi-label Classification.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Extreme Zero-Shot Learning for Extreme Text Classification.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

CAT: Customized Adversarial Training for Improved Robustness.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks.
Proceedings of the International Conference on Machine Learning, 2022

Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Improving the Adversarial Robustness of NLP Models by Information Bottleneck.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

On the Sensitivity and Stability of Model Interpretations in NLP.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Towards Adversarially Robust Text Classifiers by Learning to Reweight Clean Examples.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021
Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks.
CoRR, 2021

A Review of Adversarial Attack and Defense for Classification Methods.
CoRR, 2021

Can Vision Transformers Perform Convolution?
CoRR, 2021

Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction.
CoRR, 2021

How and When Adversarial Robustness Transfers in Knowledge Distillation?
CoRR, 2021

Adversarial Attack across Datasets.
CoRR, 2021

Training Meta-Surrogate Model for Transferable Adversarial Attack.
CoRR, 2021

Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms.
CoRR, 2021

When Vision Transformers Outperform ResNets without Pretraining or Strong Data Augmentations.
CoRR, 2021

Concurrent Adversarial Learning for Large-Batch Training.
CoRR, 2021

Balancing Robustness and Sensitivity using Feature Contrastive Learning.
CoRR, 2021

Detecting Adversarial Examples with Bayesian Neural Network.
CoRR, 2021

Deep Image Destruction: A Comprehensive Study on Vulnerability of Deep Image-to-Image Models against Adversarial Attacks.
CoRR, 2021

2.5D Visual Relationship Detection.
CoRR, 2021

On the Faithfulness Measurements for Model Interpretations.
CoRR, 2021

Fast Certified Robust Training via Better Initialization and Shorter Warmup.
CoRR, 2021

On the Adversarial Robustness of Visual Transformers.
CoRR, 2021

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Verification.
CoRR, 2021

Local Critic Training for Model-Parallel Learning of Deep Neural Networks.
CoRR, 2021

Robust Text CAPTCHAs Using Adversarial Examples.
CoRR, 2021

Communication-avoiding kernel ridge regression on parallel and distributed systems.
CCF Trans. High Perform. Comput., 2021

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fast Certified Robust Training with Short Warmup.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Label Disentanglement in Partition-based Extreme Multilabel Classification.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

DRONE: Data-aware Low-rank Compression for Large NLP Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Double Perturbation: On the Robustness of Robustness and Counterfactual Bias Evaluation.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Measures and Best Practices for Responsible AI.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Third Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2021).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Overcoming Catastrophic Forgetting by Bayesian Generative Regularization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Robust Reinforcement Learning on State Observations with Learned Optimal Adversary.
Proceedings of the 9th International Conference on Learning Representations, 2021

Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers.
Proceedings of the 9th International Conference on Learning Representations, 2021

Rethinking Architecture Selection in Differentiable NAS.
Proceedings of the 9th International Conference on Learning Representations, 2021

Evaluations and Methods for Explanation through Robustness Analysis.
Proceedings of the 9th International Conference on Learning Representations, 2021

DrNAS: Dirichlet Neural Architecture Search.
Proceedings of the 9th International Conference on Learning Representations, 2021

RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Towards Robustness of Deep Neural Networks via Regularization.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

On the Transferability of Adversarial Attacks against Neural Text Classifier.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Robust and Accurate Object Detection via Adversarial Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood Ensemble.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Multi-Proxy Wasserstein Classifier for Image Classification.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Self-Progressing Robust Training.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Emotional EEG classification using connectivity features and convolutional neural networks.
Neural Networks, 2020

Spanning attack: reinforce black-box attacks with unlabeled data.
Mach. Learn., 2020

Fast LSTM by dynamic decomposition on cloud and distributed systems.
Knowl. Inf. Syst., 2020

Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data.
J. Mach. Learn. Res., 2020

Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search.
CoRR, 2020

Voting based ensemble improves robustness of defensive models.
CoRR, 2020

Generating universal language adversarial examples by understanding and enhancing the transferability across neural models.
CoRR, 2020

How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers.
CoRR, 2020

On 𝓁<sub>p</sub>-norm Robustness of Ensemble Stumps and Trees.
CoRR, 2020

Improving the Speed and Quality of GAN by Adversarial Training.
CoRR, 2020

Defense against Adversarial Attacks in NLP via Dirichlet Neighborhood Ensemble.
CoRR, 2020

The Limit of the Batch Size.
CoRR, 2020

Robust Deep Reinforcement Learning against Adversarial Perturbations on Observations.
CoRR, 2020

Automatic Perturbation Analysis on General Computational Graphs.
CoRR, 2020

Multiscale Non-stationary Stochastic Bandits.
CoRR, 2020

Efficient Neural Interaction Function Search for Collaborative Filtering.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Clustering and Constructing User Coresets to Accelerate Large-scale Top-K Recommender Systems.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

SSE-PT: Sequential Recommendation Via Personalized Transformer.
Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

An Efficient Adversarial Attack for Tree Ensembles.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Provably Robust Metric Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Multi-Stage Influence Function.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On Lp-norm Robustness of Ensemble Decision Stumps and Trees.
Proceedings of the 37th International Conference on Machine Learning, 2020

Learning to Encode Position for Transformer with Continuous Dynamical Model.
Proceedings of the 37th International Conference on Machine Learning, 2020

Stabilizing Differentiable Architecture Search via Perturbation-based Regularization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Towards Stable and Efficient Training of Verifiably Robust Neural Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius.
Proceedings of the 8th International Conference on Learning Representations, 2020

Large Batch Optimization for Deep Learning: Training BERT in 76 minutes.
Proceedings of the 8th International Conference on Learning Representations, 2020

Robustness Verification for Transformers.
Proceedings of the 8th International Conference on Learning Representations, 2020

Learning to Learn by Zeroth-Order Oracle.
Proceedings of the 8th International Conference on Learning Representations, 2020

Sign-OPT: A Query-Efficient Hard-label Adversarial Attack.
Proceedings of the 8th International Conference on Learning Representations, 2020

Improved Adversarial Training via Learned Optimizer.
Proceedings of the Computer Vision - ECCV 2020, 2020

MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillation.
Proceedings of the Computer Vision - ECCV 2020, 2020

How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial Examples.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

What Does BERT with Vision Look At?
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Adversarially Robust Deep Image Super-Resolution Using Entropy Regularization.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

ML-LOO: Detecting Adversarial Examples with Feature Attribution.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Fast Deep Neural Network Training on Distributed Systems and Cloud TPUs.
IEEE Trans. Parallel Distributed Syst., 2019

Efficient Contextual Representation Learning With Continuous Outputs.
Trans. Assoc. Comput. Linguistics, 2019

RedSync: Reducing synchronization bandwidth for distributed deep learning training system.
J. Parallel Distributed Comput., 2019

Overcoming Catastrophic Forgetting by Generative Regularization.
CoRR, 2019

GraphDefense: Towards Robust Graph Convolutional Networks.
CoRR, 2019

Enhancing Certifiable Robustness via a Deep Model Ensemble.
CoRR, 2019

A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning.
CoRR, 2019

Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Imbalanced Data.
CoRR, 2019

Natural Adversarial Sentence Generation with Gradient-based Perturbation.
CoRR, 2019

Temporal Collaborative Ranking Via Personalized Transformer.
CoRR, 2019

VisualBERT: A Simple and Performant Baseline for Vision and Language.
CoRR, 2019

Convergence of Adversarial Training in Overparametrized Networks.
CoRR, 2019

Towards Stable and Efficient Training of Verifiably Robust Neural Networks.
CoRR, 2019

Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective.
CoRR, 2019

Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise.
CoRR, 2019

Reducing BERT Pre-Training Time from 3 Days to 76 Minutes.
CoRR, 2019

Efficient Contextual Representation Learning Without Softmax Layer.
CoRR, 2019

Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Large-batch training for LSTM and beyond.
Proceedings of the International Conference for High Performance Computing, 2019

Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Convergence of Adversarial Training in Overparametrized Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Robustness Verification of Tree-based Models.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Evaluating and Enhancing the Robustness of Dialogue Systems: A Case Study on a Negotiation Agent.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Robust Decision Trees Against Adversarial Examples.
Proceedings of the 36th International Conference on Machine Learning, 2019

The Limitations of Adversarial Training and the Blind-Spot Attack.
Proceedings of the 7th International Conference on Learning Representations, 2019

Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network.
Proceedings of the 7th International Conference on Learning Representations, 2019

Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Fast LSTM Inference by Dynamic Decomposition on Cloud Systems.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Evaluating Robustness of Deep Image Super-Resolution Against Adversarial Attacks.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

GenAttack: practical black-box attacks with gradient-free optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019

MulCode: A Multiplicative Multi-way Model for Compressing Neural Language Model.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Rob-GAN: Generator, Discriminator, and Adversarial Attacker.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

A Fast Sampling Algorithm for Maximum Inner Product Search.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

On the Robustness of Self-Attentive Models.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Using Side Information to Reliably Learn Low-Rank Matrices from Missing and Corrupted Observations.
J. Mach. Learn. Res., 2018

Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding.
CoRR, 2018

Block-wise Partitioning for Extreme Multi-label Classification.
CoRR, 2018

Attack Graph Convolutional Networks by Adding Fake Nodes.
CoRR, 2018

Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient.
CoRR, 2018

Stochastically Controlled Stochastic Gradient for the Convex and Non-convex Composition problem.
CoRR, 2018

From Adversarial Training to Generative Adversarial Networks.
CoRR, 2018

Stochastic Zeroth-order Optimization via Variance Reduction method.
CoRR, 2018

LearningWord Embeddings for Low-resource Languages by PU Learning.
CoRR, 2018

Multiple Accounts Detection on Facebook Using Semi-Supervised Learning on Graphs.
CoRR, 2018

NLRR++: Scalable Subspace Clustering via Non-Convex Block Coordinate Descent.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Efficient Neural Network Robustness Certification with General Activation Functions.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning from Group Comparisons: Exploiting Higher Order Interactions.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Word Embeddings for Low-Resource Languages by PU Learning.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Multiple Accounts Detection on Facebook Using Semi-Supervised Learning on Graphs.
Proceedings of the 2018 IEEE Military Communications Conference, 2018

Distributed Primal-Dual Optimization for Non-uniformly Distributed Data.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems.
Proceedings of the 32nd International Conference on Supercomputing, 2018

ImageNet Training in Minutes.
Proceedings of the 47th International Conference on Parallel Processing, 2018

SQL-Rank: A Listwise Approach to Collaborative Ranking.
Proceedings of the 35th International Conference on Machine Learning, 2018

Towards Fast Computation of Certified Robustness for ReLU Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

Fast Variance Reduction Method with Stochastic Batch Size.
Proceedings of the 35th International Conference on Machine Learning, 2018

Extreme Learning to Rank via Low Rank Assumption.
Proceedings of the 35th International Conference on Machine Learning, 2018

Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach.
Proceedings of the 6th International Conference on Learning Representations, 2018

On Extensions of Clever: A Neural Network Robustness Evaluation Algorithm.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Towards Robust Neural Networks via Random Self-ensemble.
Proceedings of the Computer Vision - ECCV 2018, 2018

Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Memory Efficient Kernel Approximation.
J. Mach. Learn. Res., 2017

Show-and-Fool: Crafting Adversarial Examples for Neural Image Captioning.
CoRR, 2017

100-epoch ImageNet Training with AlexNet in 24 Minutes.
CoRR, 2017

An inexact subsampled proximal Newton-type method for large-scale machine learning.
CoRR, 2017

GPU-acceleration for Large-scale Tree Boosting.
CoRR, 2017

Positive-Unlabeled Demand-Aware Recommendation.
CoRR, 2017

A Greedy Approach for Budgeted Maximum Inner Product Search.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Scalable Demand-Aware Recommendation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Large-scale Collaborative Ranking in Near-Linear Time.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Improved Bounded Matrix Completion for Large-Scale Recommender Systems.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Computable Expert Knowledge in Computer Games.
Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

Gradient Boosted Decision Trees for High Dimensional Sparse Output.
Proceedings of the 34th International Conference on Machine Learning, 2017

A Hyperplane-Based Algorithm for Semi-Supervised Dimension Reduction.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

ZOO: Zeroth Order Optimization Based Black-box Attacks to Deep Neural Networks without Training Substitute Models.
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, 2017

Rank Aggregation and Prediction with Item Features.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Machine Learning Meliorates Computing and Robustness in Discrete Combinatorial Optimization Problems.
Frontiers Appl. Math. Stat., 2016

Communication-Efficient Parallel Block Minimization for Kernel Machines.
CoRR, 2016

Nomadic Computing for Big Data Analytics.
Computer, 2016

Asynchronous Parallel Greedy Coordinate Descent.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Goal-Directed Inductive Matrix Completion.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Computationally Efficient Nyström Approximation using Fast Transforms.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Robust Principal Component Analysis with Side Information.
Proceedings of the 33nd International Conference on Machine Learning, 2016

HogWild++: A New Mechanism for Decentralized Asynchronous Stochastic Gradient Descent.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Fixing the Convergence Problems in Parallel Asynchronous Dual Coordinate Descent.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015
A Scalable Asynchronous Distributed Algorithm for Topic Modeling.
Proceedings of the 24th International Conference on World Wide Web, 2015

Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Matrix Completion with Noisy Side Information.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent.
Proceedings of the 32nd International Conference on Machine Learning, 2015

PU Learning for Matrix Completion.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion.
Proc. VLDB Endow., 2014

Parallel matrix factorization for recommender systems.
Knowl. Inf. Syst., 2014

QUIC: quadratic approximation for sparse inverse covariance estimation.
J. Mach. Learn. Res., 2014

Prediction and clustering in signed networks: a local to global perspective.
J. Mach. Learn. Res., 2014

Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Fast Prediction for Large-Scale Kernel Machines.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

A Divide-and-Conquer Solver for Kernel Support Vector Machines.
Proceedings of the 31th International Conference on Machine Learning, 2014

Nuclear Norm Minimization via Active Subspace Selection.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion.
CoRR, 2013

Organizational overlap on social networks and its applications.
Proceedings of the 22nd International World Wide Web Conference, 2013

Large Scale Distributed Sparse Precision Estimation.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012
Large Linear Classification When Data Cannot Fit in Memory.
ACM Trans. Knowl. Discov. Data, 2012

A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Sparse inverse covariance matrix estimation using quadratic approximation.
Proceedings of the 2012 Symposium on Machine Learning in Speech and Language Processing, 2012

Low rank modeling of signed networks.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

2011
Fast coordinate descent methods with variable selection for non-negative matrix factorization.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

2010
A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification.
J. Mach. Learn. Res., 2010

Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models
J. Mach. Learn. Res., 2010

Training and Testing Low-degree Polynomial Data Mappings via Linear SVM.
J. Mach. Learn. Res., 2010

2009
An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes.
Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009, 2009

Iterative Scaling and Coordinate Descent Methods for Maximum Entropy.
Proceedings of the ACL 2009, 2009

2008
LIBLINEAR: A Library for Large Linear Classification.
J. Mach. Learn. Res., 2008

Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines.
J. Mach. Learn. Res., 2008

A sequential dual method for large scale multi-class linear svms.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

A dual coordinate descent method for large-scale linear SVM.
Proceedings of the Machine Learning, 2008


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