← Authors

Ji Liu

99 papers · 2010–2026 · 14 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (23) 🧭 Keyword Pioneer 🌍 Conference Polyglot (14) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (6) 🐝 Cross-Pollinator (15) πŸƒ Academic Marathon (15) πŸŒ‰ Interdisciplinary Bridge 🏠 Conference Loyalist (23) 🧬 Topic Evolution πŸ”¬ Deep Specialist (39) 🀝 Dynamic Duo (13) πŸ† Grand Slam πŸ† Keyword Champion (2) πŸ‘‘ Triple Crown πŸ“ˆ Trend Setter ❓ The Questioner ⚑ Prolific Year (8) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (84) πŸ’Ž Century Club (97) πŸ”₯ Unstoppable (14)

Conferences

NIPS (23) ICML (16) AAAI (15) CVPR (9) ICLR (6) IJCAI (6) ICCV (5) AISTATS (4) ECCV (4) JMLR (4) EMNLP (3) ACL (2) IJCNLP (1) NAACL (1)

Top co-authors

Xiangru Lian (13) Dejing Dou (11) Dong Li (10) Ce Zhang (10) Lu Tian (9) Haichuan Yang (8) Jianchao Tan (8) Yang Zhou (8) Sen Yang (7) Hanlin Tang (6)

Research topics

Education (1)

Keywords

model compression (13) distributed learning (10) reinforcement learning (8) feature selection (7) federated learning (7) stochastic optimization (6) stochastic gradient descent (6) convex optimization (6) neural network (5) neural network optimization (5) variance reduction (4) compositional optimization (4) linear convergence (4) convolutional neural network (4) gradient descent (4) compressed sensing (4) communication efficiency (4) deep neural network (4) stochastic gradient (3) model pruning (3)

Papers

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