Dawen Liang - RankMe

54 papers A* 10A 7Misc 2Journal 22Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents. ICML Kaiwen Wang, Dawen Liang, Nathan Kallus, Wen Sun
2025	A*	`conf`	Collaborative Retrieval for Large Language Model-based Conversational Recommender Systems. WWW Yaochen Zhu, Chao Wan, Harald Steck, Dawen Liang, Yesu Feng, Nathan Kallus, Jundong Li
2025	J	`jnl`	Collaborative Retrieval for Large Language Model-based Conversational Recommender Systems. CoRR Yaochen Zhu, Chao Wan, Harald Steck, Dawen Liang, Yesu Feng, Nathan Kallus, Jundong Li
2025	J	`jnl`	DiFFPO: Training Diffusion LLMs to Reason Fast and Furious via Reinforcement Learning. CoRR Hanyang Zhao, Dawen Liang, Wenpin Tang, David D. Yao, Nathan Kallus
2025	A*	`conf`	Does Weighting Improve Matrix Factorization for Recommender Systems? WWW Alex Ayoub, Samuel Robertson, Dawen Liang, Harald Steck, Nathan Kallus
2025	J	`jnl`	Does Weighting Improve Matrix Factorization for Recommender Systems? CoRR Alex Ayoub, Samuel Robertson, Dawen Liang, Harald Steck, Nathan Kallus
2025	J	`jnl`	From Reviews to Dialogues: Active Synthesis for Zero-Shot LLM-based Conversational Recommender System. CoRR Rohan Surana, Junda Wu, Zhouhang Xie, Yu Xia, Harald Steck, Dawen Liang, Nathan Kallus, Julian J. McAuley
2025	—	`conf`	LLM-based Conversational Recommendation Agents with Collaborative Verbalized Experience. EMNLP (Findings) Yaochen Zhu, Harald Steck, Dawen Liang, Yinhan He, Nathan Kallus, Jundong Li
2025	J	`jnl`	Rank-GRPO: Training LLM-based Conversational Recommender Systems with Reinforcement Learning. CoRR Yaochen Zhu, Harald Steck, Dawen Liang, Yinhan He, Vito Ostuni, Jundong Li, Nathan Kallus
2025	A	`conf`	Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation. WSDM Zhankui He, Zhouhang Xie, Harald Steck, Dawen Liang, Rahul Jha, Nathan Kallus, Julian J. McAuley
2024	A	`conf`	Neighborhood-Based Collaborative Filtering for Conversational Recommendation. RecSys Zhouhang Xie, Junda Wu, Hyunsik Jeon, Zhankui He, Harald Steck, Rahul Jha, Dawen Liang, Nathan Kallus, Julian J. McAuley
2024	A*	`conf`	Off-Policy Evaluation for Large Action Spaces via Policy Convolution. WWW Noveen Sachdeva, Lequn Wang, Dawen Liang, Nathan Kallus, Julian J. McAuley
2024	J	`jnl`	Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation. CoRR Zhankui He, Zhouhang Xie, Harald Steck, Dawen Liang, Rahul Jha, Nathan Kallus, Julian J. McAuley
2024	J	`jnl`	Risk-Sensitive RL with Optimized Certainty Equivalents via Reduction to Standard RL. CoRR Kaiwen Wang, Dawen Liang, Nathan Kallus, Wen Sun
2024	A*	`conf`	Switching the Loss Reduces the Cost in Batch Reinforcement Learning. ICML Alex Ayoub, Kaiwen Wang, Vincent Liu, Samuel Robertson, James McInerney, Dawen Liang, Nathan Kallus, Csaba Szepesvári
2024	J	`jnl`	Switching the Loss Reduces the Cost in Batch Reinforcement Learning. CoRR Alex Ayoub, Kaiwen Wang, Vincent Liu, Samuel Robertson, James McInerney, Dawen Liang, Nathan Kallus, Csaba Szepesvári
2023	A	`conf`	Large Language Models as Zero-Shot Conversational Recommenders. CIKM Zhankui He, Zhouhang Xie, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Prasad Majumder, Nathan Kallus, Julian J. McAuley
2023	J	`jnl`	Large Language Models as Zero-Shot Conversational Recommenders. CoRR Zhankui He, Zhouhang Xie, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Prasad Majumder, Nathan Kallus, Julian J. McAuley
2023	J	`jnl`	Off-Policy Evaluation for Large Action Spaces via Policy Convolution. CoRR Noveen Sachdeva, Lequn Wang, Dawen Liang, Nathan Kallus, Julian J. McAuley
2022	J	`jnl`	Local Policy Improvement for Recommender Systems. CoRR Dawen Liang, Nikos Vlassis
2021	A*	`conf`	Bayesian Causal Inference for Real World Interactive Systems. KDD Nicolas Chopin, Mike Gartrell, Dawen Liang, Alberto Lumbreras, David Rohde, Yixin Wang
2021	J	`jnl`	Deep Learning for Recommender Systems: A Netflix Case Study. AI Mag. Harald Steck, Linas Baltrunas, Ehtsham Elahi, Dawen Liang, Yves Raimond, Justin Basilico
2021	A	`conf`	Negative Interactions for Improved Collaborative Filtering: Don't go Deeper, go Higher. RecSys Harald Steck, Dawen Liang
2020	A	`conf`	Causal Inference for Recommender Systems. RecSys Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei
2020	—	`ed.`	Symposium on Advances in Approximate Bayesian Inference, AABI 2019, Vancouver, BC, Canada, December 8, 2019. AABI Cheng Zhang, Francisco J. R. Ruiz, Thang D. Bui, Adji Bousso Dieng, Dawen Liang
2019	—	`conf`	Correlated Variational Auto-Encoders. DGS@ICLR Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
2019	A*	`conf`	Correlated Variational Auto-Encoders. ICML Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
2019	J	`jnl`	Correlated Variational Auto-Encoders. CoRR Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
2019	J	`jnl`	Learning Correlated Latent Representations with Adaptive Priors. CoRR Da Tang, Dawen Liang, Nicholas Ruozzi, Tony Jebara
2019	—	`ed.`	Symposium on Advances in Approximate Bayesian Inference, AABI 2018, Montréal, QC, Canada, December 2, 2018. AABI Francisco J. R. Ruiz, Cheng Zhang, Dawen Liang, Thang D. Bui
2018	A	`conf`	On the challenges of learning with inference networks on sparse, high-dimensional data. AISTATS Rahul G. Krishnan, Dawen Liang, Matthew D. Hoffman
2018	J	`jnl`	The Deconfounded Recommender: A Causal Inference Approach to Recommendation. CoRR Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei
2018	A*	`conf`	Variational Autoencoders for Collaborative Filtering. WWW Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, Tony Jebara
2018	J	`jnl`	Variational Autoencoders for Collaborative Filtering. CoRR Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, Tony Jebara
2017	J	`jnl`	On the challenges of learning with inference networks on sparse, high-dimensional data. CoRR Rahul G. Krishnan, Dawen Liang, Matthew D. Hoffman
2016	J	`jnl`	Edward: A library for probabilistic modeling, inference, and criticism. CoRR Dustin Tran, Alp Kucukelbir, Adji B. Dieng, Maja Rudolph, Dawen Liang, David M. Blei
2016	A	`conf`	Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Co-occurrence. RecSys Dawen Liang, Jaan Altosaar, Laurent Charlin, David M. Blei
2016	A*	`conf`	Modeling User Exposure in Recommendation. WWW Dawen Liang, Laurent Charlin, James McInerney, David M. Blei
2016	—	`—`	Understanding Music Semantics and User Behavior with Probabilistic Latent Variable Models. Dawen Liang
2015	—	`conf`	Content-Aware Collaborative Music Recommendation Using Pre-trained Neural Networks. ISMIR Dawen Liang, Minshu Zhan, Daniel P. W. Ellis
2015	A*	`conf`	Landmarking Manifolds with Gaussian Processes. ICML Dawen Liang, John W. Paisley
2015	J	`jnl`	Modeling User Exposure in Recommendation. CoRR Dawen Liang, Laurent Charlin, James McInerney, David M. Blei
2015	Misc	`conf`	Speech dereverberation using a learned speech model. ICASSP Dawen Liang, Matthew D. Hoffman, Gautham J. Mysore
2015	—	`conf`	librosa: Audio and Music Signal Analysis in Python. SciPy Brian McFee, Colin Raffel, Dawen Liang, Daniel P. W. Ellis, Matt McVicar, Eric Battenberg, Oriol Nieto
2014	—	`conf`	A Generative Product-of-Filters Model of Audio. ICLR (Poster) Dawen Liang, Matthew D. Hoffman, Gautham J. Mysore
2014	J	`jnl`	Active Scores: Representation and Synchronization in Human-Computer Performance of Popular Music. Comput. Music. J. Roger B. Dannenberg, Nicolas E. Gold, Dawen Liang, Guangyu Xia
2014	J	`jnl`	Beta Process Non-negative Matrix Factorization with Stochastic Structured Mean-Field Variational Inference. CoRR Dawen Liang, Matthew D. Hoffman
2014	—	`conf`	Codebook-based Scalable Music Tagging with Poisson Matrix Factorization. ISMIR Dawen Liang, John W. Paisley, Dan Ellis
2014	—	`conf`	MIR_EVAL: A Transparent Implementation of Common MIR Metrics. ISMIR Colin Raffel, Brian McFee, Eric J. Humphrey, Justin Salamon, Oriol Nieto, Dawen Liang, Daniel P. W. Ellis
2014	J	`jnl`	Methods and Prospects for Human-Computer Performance of Popular Music. Comput. Music. J. Roger B. Dannenberg, Nicolas E. Gold, Dawen Liang, Guangyu Xia
2014	Misc	`conf`	Speech decoloration based on the product-of-filters model. ICASSP Dawen Liang, Daniel P. W. Ellis, Matthew D. Hoffman, Gautham J. Mysore
2013	—	`conf`	Beta Process Sparse Nonnegative Matrix Factorization for Music. ISMIR Dawen Liang, Matthew D. Hoffman, Daniel P. W. Ellis
2011	—	`conf`	A Framework for Coordination and Synchronization of Media. NIME Dawen Liang, Guangyu Xia, Roger B. Dannenberg
2011	—	`conf`	Segmentation, Clustering, and Display in a Personal Audio Database for Musicians. ISMIR Guangyu Xia, Dawen Liang, Roger B. Dannenberg, Mark Harvilla