Ji Liu

DiffBench Meets DiffAgent: End-to-End LLM-Driven Diffusion Acceleration Code Generation AAAI 2026 Learnable Permutation for Structured Sparsity on Transformer Models AAAI 2026 SGDPO: Self-Guided Direct Preference Optimization for Language Model Alignment ACL 2025 Amphista: Bi-directional Multi-head Decoding for Accelerating LLM Inference NAACL 2025 CARFT: Boosting LLM Reasoning via Contrastive Learning with Annotated Chain-of-Thought-based Reinforced Fine-Tuning EMNLP 2025 EGSRAL:An Enhanced 3D Gaussian Splatting Based Renderer with Automated Labeling for Large-Scale Driving Scene AAAI 2025 Sampling-based Safe Reinforcement Learning for Nonlinear Dynamical Systems AISTATS 2024 G–LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint) AAAI 2024 FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update AAAI 2024 UPDP: A Unified Progressive Depth Pruner for CNN and Vision Transformer AAAI 2024 DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization NIPS 2024 Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models EMNLP 2024 LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising CVPR 2023 Pixel Adaptive Deep Unfolding Transformer for Hyperspectral Image Reconstruction ICCV 2023 Quality-Aware Self-Training on Differentiable Synthesis of Rare Relational Data AAAI 2023 PINAT: A Permutation INvariance Augmented Transformer for NAS Predictor AAAI 2023 ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-Cost Proxies AAAI 2023 Accurate MRI Reconstruction via Multi-Domain Recurrent Networks IJCAI 2023 Fast Federated Machine Unlearning with Nonlinear Functional Theory ICML 2023 Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising CVPR 2023 Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization EMNLP 2023 Improving Certified Robustness via Statistical Learning with Logical Reasoning NIPS 2022 Efficient Device Scheduling with Multi-Job Federated Learning AAAI 2022 Accelerated Federated Learning with Decoupled Adaptive Optimization ICML 2022 Unified Visual Transformer Compression ICLR 2022 Multi-Granularity Pruning for Model Acceleration on Mobile Devices ECCV 2022 FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server IJCAI 2022 Bandwidth-Aware Adaptive Codec for DNN Inference Offloading in IoT ECCV 2022 Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification CVPR 2022 Dynamic Sparse R-CNN CVPR 2022 ResRep: Lossless CNN Pruning via Decoupling Remembering and Forgetting ICCV 2021 RankDetNet: Delving Into Ranking Constraints for Object Detection CVPR 2021 ErrorCompensatedX: error compensation for variance reduced algorithms NIPS 2021 Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory NIPS 2021 1-bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed ICML 2021 Incorporating Global Information in Local Attention for Knowledge Representation Learning IJCNLP 2021 Optimizing Information Theory Based Bitwise Bottlenecks for Efficient Mixed-Precision Activation Quantization AAAI 2021 C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak AAAI 2021 Improving Low-Precision Network Quantization via Bin Regularization ICCV 2021 UMEC: Unified model and embedding compression for efficient recommendation systems ICLR 2021 DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning ICML 2021 Streaming Bayesian Deep Tensor Factorization ICML 2021 Incorporating Global Information in Local Attention for Knowledge Representation Learning ACL 2021 GDP: Stabilized Neural Network Pruning via Gates With Differentiable Polarization ICCV 2021 Reinforcement Learning for Cost-Aware Markov Decision Processes ICML 2021 Shifted Chunk Transformer for Spatio-Temporal Representational Learning NIPS 2021 Hand Image Understanding via Deep Multi-Task Learning ICCV 2021 Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments ICLR 2021 TNASP: A Transformer-based NAS Predictor with a Self-evolution Framework NIPS 2021 Hand-Transformer: Non-Autoregressive Structured Modeling for 3D Hand Pose Estimation ECCV 2020 Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free NIPS 2020 Watch the Unobserved: A Simple Approach to Parallelizing Monte Carlo Tree Search ICLR 2020 IMRAM: Iterative Matching With Recurrent Attention Memory for Cross-Modal Image-Text Retrieval CVPR 2020 Deep Embedded Complementary and Interactive Information for Multi-View Classification AAAI 2020 GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework ECCV 2020 Feature Variance Regularization: A Simple Way to Improve the Generalizability of Neural Networks AAAI 2020 Automatic Neural Network Compression by Sparsity-Quantization Joint Learning: A Constrained Optimization-Based Approach CVPR 2020 LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning NIPS 2019 Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent NIPS 2019 Model Compression with Adversarial Robustness: A Unified Optimization Framework NIPS 2019 Global Sparse Momentum SGD for Pruning Very Deep Neural Networks NIPS 2019 Optimal Projection Guided Transfer Hashing for Image Retrieval AAAI 2019 AutoML from Service Provider’s Perspective: Multi-device, Multi-tenant Model Selection with GP-EI AISTATS 2019 Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization AISTATS 2019 ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model CVPR 2019 Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking ICLR 2019 Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications ICLR 2019 DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression ICML 2019 Distributed Learning over Unreliable Networks ICML 2019 Communication Compression for Decentralized Training NIPS 2018 Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity NIPS 2018 Asynchronous Decentralized Parallel Stochastic Gradient Descent ICML 2018 $D^2$: Decentralized Training over Decentralized Data ICML 2018 New Balanced Active Learning Model and Optimization Algorithm IJCAI 2018 Gradient Sparsification for Communication-Efficient Distributed Optimization NIPS 2018 Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent NIPS 2017 No Learner Left Behind: On the Complexity of Teaching Multiple Learners Simultaneously IJCAI 2017 Accelerating Stochastic Composition Optimization JMLR 2017 Finite-sum Composition Optimization via Variance Reduced Gradient Descent AISTATS 2017 On The Projection Operator to A Three-view Cardinality Constrained Set ICML 2017 ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning ICML 2017 A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order NIPS 2016 The Teaching Dimension of Linear Learners ICML 2016 Staleness-Aware Async-SGD for Distributed Deep Learning IJCAI 2016 Proximal Gradient Temporal Difference Learning Algorithms IJCAI 2016 Accelerating Stochastic Composition Optimization NIPS 2016 Asynchronous Parallel Greedy Coordinate Descent NIPS 2016 The Teaching Dimension of Linear Learners JMLR 2016 On Benefits of Selection Diversity via Bilevel Exclusive Sparsity CVPR 2016 An Asynchronous Parallel Stochastic Coordinate Descent Algorithm JMLR 2015 Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization NIPS 2015 Exclusive Feature Learning on Arbitrary Structures via $\ell_{1,2}$-norm NIPS 2014 An Asynchronous Parallel Stochastic Coordinate Descent Algorithm ICML 2014 Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint ICML 2014 An Approximate, Efficient LP Solver for LP Rounding NIPS 2013 Guaranteed Sparse Recovery under Linear Transformation ICML 2013 Regularized Off-Policy TD-Learning NIPS 2012 A Multi-Stage Framework for Dantzig Selector and LASSO JMLR 2012 Multi-Stage Dantzig Selector NIPS 2010