Enmao Diao - RankMe

55 papers A* 7A 2B 4Misc 2Journal 34Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Kinetic-Energy Perspective of Flow Matching. CoRR Ziyun Li, Huancheng Hu, Soon Hoe Lim, Xuyu Li, Fei Gao, Enmao Diao, Zezhen Ding, Michalis Vazirgiannis, Henrik Boström
2026	J	`jnl`	Graph Tokenization for Bridging Graphs and Transformers. CoRR Zeyuan Guo, Enmao Diao, Cheng Yang, Chuan Shi
2025	—	`conf`	AID: Adaptive Integration of Detectors for Safe AI with Language Models. NAACL (Long Papers) Xinran Wang, Enmao Diao, Qi Le, Jie Ding, Ali Anwar
2025	J	`jnl`	From Local to Global: Revisiting Structured Pruning Paradigms for Large Language Models. CoRR Ziyan Wang, Enmao Diao, Qi Le, Pu Wang, Minwoo Lee, Shu-Ping Yeh, Evgeny Stupachenko, Hao Feng, Li Yang
2025	A*	`conf`	MAP: Multi-Human-Value Alignment Palette. ICLR Xinran Wang, Qi Le, Ammar Ahmed, Enmao Diao, Yi Zhou, Nathalie Baracaldo, Jie Ding, Ali Anwar
2025	J	`jnl`	OBCache: Optimal Brain KV Cache Pruning for Efficient Long-Context LLM Inference. CoRR Yuzhe Gu, Xiyu Liang, Jiaojiao Zhao, Enmao Diao
2025	A*	`conf`	Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing. ICLR Qi Le, Enmao Diao, Ziyan Wang, Xinran Wang, Jie Ding, Li Yang, Ali Anwar
2025	J	`jnl`	Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing. CoRR Qi Le, Enmao Diao, Ziyan Wang, Xinran Wang, Jie Ding, Li Yang, Ali Anwar
2025	J	`jnl`	Robust Score-Based Quickest Change Detection. IEEE Trans. Inf. Theory Sean Moushegian, Suya Wu, Enmao Diao, Jie Ding, Taposh Banerjee, Vahid Tarokh
2025	J	`jnl`	Think Before You Prune: Self-Reflective Structured Pruning for Reasoning Language Models. CoRR Ziyan Wang, Enmao Diao, Qi Le, Pu Wang, Guanchu Wang, Minwoo Lee, Shu-Ping Yeh, Li Yang
2025	J	`jnl`	Toward Unifying Group Fairness Evaluation from a Sparsity Perspective. CoRR Zhecheng Sheng, Jiawei Zhang, Enmao Diao
2024	J	`jnl`	A Data-Efficient Deep Learning Method for Rough Surface Clutter Reduction in GPR Images. IEEE Trans. Geosci. Remote. Sens. Yan Zhang, Enmao Diao, Dryver Huston, Tian Xia
2024	J	`jnl`	ColA: Collaborative Adaptation with Gradient Learning. CoRR Enmao Diao, Qi Le, Suya Wu, Xinran Wang, Ali Anwar, Jie Ding, Vahid Tarokh
2024	B	`conf`	DynamicFL: Federated Learning with Dynamic Communication Resource Allocation. IEEE Big Data Qi Le, Enmao Diao, Xinran Wang, Ahmad Faraz Khan, Vahid Tarokh, Jie Ding, Ali Anwar
2024	J	`jnl`	DynamicFL: Federated Learning with Dynamic Communication Resource Allocation. CoRR Qi Le, Enmao Diao, Xinran Wang, Vahid Tarokh, Jie Ding, Ali Anwar
2024	A*	`conf`	ESC: Efficient Speech Coding with Cross-Scale Residual Vector Quantized Transformers. EMNLP Yuzhe Gu, Enmao Diao
2024	J	`jnl`	ESC: Efficient Speech Coding with Cross-Scale Residual Vector Quantized Transformers. CoRR Yuzhe Gu, Enmao Diao
2024	J	`jnl`	Large Deviation Analysis of Score-Based Hypothesis Testing. IEEE Access Enmao Diao, Taposh Banerjee, Vahid Tarokh
2024	J	`jnl`	MAP: Multi-Human-Value Alignment Palette. CoRR Xinran Wang, Qi Le, Ammar Ahmed, Enmao Diao, Yi Zhou, Nathalie Baracaldo, Jie Ding, Ali Anwar
2024	J	`jnl`	Quickest Change Detection for Unnormalized Statistical Models. IEEE Trans. Inf. Theory Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh
2023	—	`—`	Efficient and Collaborative Methods for Distributed Machine Learning. Enmao Diao
2023	A*	`conf`	Pruning Deep Neural Networks from a Sparsity Perspective. ICLR Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh
2023	J	`jnl`	Pruning Deep Neural Networks from a Sparsity Perspective. CoRR Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh
2023	J	`jnl`	Quickest Change Detection for Unnormalized Statistical Models. CoRR Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh
2023	A	`conf`	Robust Quickest Change Detection for Unnormalized Models. UAI Suya Wu, Enmao Diao, Jie Ding, Taposh Banerjee, Vahid Tarokh
2023	A	`conf`	Score-based Quickest Change Detection for Unnormalized Models. AISTATS Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh
2023	—	`conf`	Semi-Supervised Federated Learning for Keyword Spotting. ICME Workshops Enmao Diao, Eric W. Tramel, Jie Ding, Tao Zhang
2023	J	`jnl`	Semi-Supervised Federated Learning for Keyword Spotting. CoRR Enmao Diao, Eric W. Tramel, Jie Ding, Tao Zhang
2022	B	`conf`	A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow. DCC Mohammadreza Momenifar, Enmao Diao, Vahid Tarokh, Andrew D. Bragg
2022	J	`jnl`	A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow. CoRR Mohammadreza Momenifar, Enmao Diao, Vahid Tarokh, Andrew D. Bragg
2022	J	`jnl`	A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation. CoRR Wenjing Yang, Ganghua Wang, Enmao Diao, Vahid Tarokh, Jie Ding, Yuhong Yang
2022	A*	`conf`	GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations. NeurIPS Enmao Diao, Jie Ding, Vahid Tarokh
2022	—	`conf`	Multimodal Controller for Generative Models. CVMI Enmao Diao, Jie Ding, Vahid Tarokh
2022	—	`conf`	Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders. IEEECONF Qi Le, Enmao Diao, Xinran Wang, Ali Anwar, Vahid Tarokh, Jie Ding
2022	J	`jnl`	Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders. CoRR Qi Le, Enmao Diao, Xinran Wang, Ali Anwar, Vahid Tarokh, Jie Ding
2022	J	`jnl`	Score-Based Hypothesis Testing for Unnormalized Models. IEEE Access Suya Wu, Enmao Diao, Khalil Elkhalil, Jie Ding, Vahid Tarokh
2022	A*	`conf`	SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training. NeurIPS Enmao Diao, Jie Ding, Vahid Tarokh
2021	J	`jnl`	Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning Models. CoRR Mohammadreza Momenifar, Enmao Diao, Vahid Tarokh, Andrew D. Bragg
2021	J	`jnl`	Gradient Assisted Learning. CoRR Enmao Diao, Jie Ding, Vahid Tarokh
2021	A*	`conf`	HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients. ICLR Enmao Diao, Jie Ding, Vahid Tarokh
2021	J	`jnl`	On Statistical Efficiency in Learning. IEEE Trans. Inf. Theory Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh
2021	J	`jnl`	Privacy-Preserving Multi-Target Multi-Domain Recommender Systems with Assisted AutoEncoders. CoRR Enmao Diao, Vahid Tarokh, Jie Ding
2021	J	`jnl`	SemiFL: Communication Efficient Semi-Supervised Federated Learning with Unlabeled Clients. CoRR Enmao Diao, Jie Ding, Vahid Tarokh
2020	B	`conf`	DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression. DCC Enmao Diao, Jie Ding, Vahid Tarokh
2020	B	`conf`	Deep Clustering of Compressed Variational Embeddings. DCC Suya Wu, Enmao Diao, Jie Ding, Vahid Tarokh
2020	J	`jnl`	HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients. CoRR Enmao Diao, Jie Ding, Vahid Tarokh
2020	J	`jnl`	Multimodal Controller for Generative Models. CoRR Enmao Diao, Jie Ding, Vahid Tarokh
2020	J	`jnl`	On Statistical Efficiency in Learning. CoRR Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh
2020	Misc	`conf`	Speech Emotion Recognition with Dual-Sequence LSTM Architecture. ICASSP Jianyou Wang, Michael Xue, Ryan Culhane, Enmao Diao, Jie Ding, Vahid Tarokh
2019	J	`jnl`	Deep Clustering of Compressed Variational Embeddings. CoRR Suya Wu, Enmao Diao, Jie Ding, Vahid Tarokh
2019	J	`jnl`	Distributed Lossy Image Compression with Recurrent Networks. CoRR Enmao Diao, Jie Ding, Vahid Tarokh
2019	—	`conf`	Restricted Recurrent Neural Networks. IEEE BigData Enmao Diao, Jie Ding, Vahid Tarokh
2019	J	`jnl`	Restricted Recurrent Neural Networks. CoRR Enmao Diao, Jie Ding, Vahid Tarokh
2019	J	`jnl`	Speech Emotion Recognition with Dual-Sequence LSTM Architecture. CoRR Jianyou Wang, Michael Xue, Ryan Culhane, Enmao Diao, Jie Ding, Vahid Tarokh
2018	Misc	`conf`	A Penalized Method for the Predictive Limit of Learning. ICASSP Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh