Yi Xu

Cost-Sensitive Conformal Training with Provably Controllable Learning Bounds AAAI 2026 Distillation-Guided Structural Transfer for Continual Learning Beyond Sparse Distributed Memory AAAI 2026 Score-Based Model for Low-Rank Tensor Recovery AAAI 2026 BIG-FUSION: Brain-Inspired Global-Local Context Fusion Framework for Multimodal Emotion Recognition in Conversations AAAI 2025 ConformalSAM: Unlocking the Potential of Foundational Segmentation Models in Semi-Supervised Semantic Segmentation with Conformal Prediction ICCV 2025 Efficient ANN-SNN Conversion with Error Compensation Learning ICML 2025 SpikingYOLOX: Improved YOLOX Object Detection with Fast Fourier Convolution and Spiking Neural Networks AAAI 2025 Diverse and Stable 2D Diffusion Guided Text to 3D Generation with Noise Recalibration AAAI 2024 Learn to Optimize Denoising Scores: A Unified and Improved Diffusion Prior for 3D Generation ECCV 2024 ParCo: Part-Coordinating Text-to-Motion Synthesis ECCV 2024 The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks ICML 2024 In-sample Actor Critic for Offline Reinforcement Learning ICLR 2023 Supported Trust Region Optimization for Offline Reinforcement Learning ICML 2023 Supported Value Regularization for Offline Reinforcement Learning NeurIPS 2023 TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization CVPR 2023 CHEX: CHannel EXploration for CNN Model Compression CVPR 2022 Effective Model Sparsification by Scheduled Grow-and-Prune Methods ICLR 2022 Improved Fine-Tuning by Better Leveraging Pre-Training Data NeurIPS 2022 Learning From Untrimmed Videos: Self-Supervised Video Representation Learning With Hierarchical Consistency CVPR 2022 An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives NeurIPS 2021 Dash: Semi-Supervised Learning with Dynamic Thresholding ICML 2021 Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity ICML 2021 Optimal Epoch Stochastic Gradient Descent Ascent Methods for Min-Max Optimization NeurIPS 2020 Stochastic Optimization for Non-convex Inf-Projection Problems ICML 2020 Katalyst: Boosting Convex Katayusha for Non-Convex Problems with a Large Condition Number ICML 2019 Learning with Non-Convex Truncated Losses by SGD UAI 2019 Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems NeurIPS 2019 On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization IJCAI 2019 Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence ICML 2019 First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time NeurIPS 2018 SADAGRAD: Strongly Adaptive Stochastic Gradient Methods ICML 2018 ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization NeurIPS 2017 Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth Parameter NeurIPS 2017 Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence ICML 2017 Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than O(1/ε) NeurIPS 2016