Hanjun Dai - RankMe

134 papers A* 50A 5B 1Journal 65Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Expectations: Learning with Stochastic Dominance Made Practical. Trans. Mach. Learn. Res. Shicong Cen, Jincheng Mei, Hanjun Dai, Dale Schuurmans, Yuejie Chi, Bo Dai
2025	J	`jnl`	AmorLIP: Efficient Language-Image Pretraining via Amortization. CoRR Haotian Sun, Yitong Li, Yuchen Zhuang, Niao He, Hanjun Dai, Bo Dai
2025	A	`conf`	Faster WIND: Accelerating Iterative Best-of-N Distillation for LLM Alignment. AISTATS Tong Yang, Jincheng Mei, Hanjun Dai, Zixin Wen, Shicong Cen, Dale Schuurmans, Yuejie Chi, Bo Dai
2025	J	`jnl`	Towards Better Instruction Following Retrieval Models. CoRR Yuchen Zhuang, Aaron Trinh, Rushi Qiang, Haotian Sun, Chao Zhang, Hanjun Dai, Bo Dai
2025	A*	`conf`	Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF. ICLR Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai
2024	J	`jnl`	Autoregressive Large Language Models are Computationally Universal. CoRR Dale Schuurmans, Hanjun Dai, Francesco Zanini
2024	J	`jnl`	Beyond Expectations: Learning with Stochastic Dominance Made Practical. CoRR Shicong Cen, Jincheng Mei, Hanjun Dai, Dale Schuurmans, Yuejie Chi, Bo Dai
2024	J	`jnl`	Exploring and Benchmarking the Planning Capabilities of Large Language Models. CoRR Bernd Bohnet, Azade Nova, Aaron T. Parisi, Kevin Swersky, Katayoon Goshvadi, Hanjun Dai, Dale Schuurmans, Noah Fiedel, Hanie Sedghi
2024	J	`jnl`	Faster WIND: Accelerating Iterative Best-of- CoRR Tong Yang, Jincheng Mei, Hanjun Dai, Zixin Wen, Shicong Cen, Dale Schuurmans, Yuejie Chi, Bo Dai
2024	J	`jnl`	Matryoshka: Learning to Drive Black-Box LLMs with LLMs. CoRR Changhao Li, Yuchen Zhuang, Rushi Qiang, Haotian Sun, Hanjun Dai, Chao Zhang, Bo Dai
2024	A*	`conf`	Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models. ICML Songtao Liu, Hanjun Dai, Yue Zhao, Peng Liu
2024	J	`jnl`	Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models. CoRR Songtao Liu, Hanjun Dai, Yue Zhao, Peng Liu
2024	J	`jnl`	SDDBench: A Benchmark for Synthesizable Drug Design. CoRR Songtao Liu, Zhengkai Tu, Hanjun Dai, Peng Liu
2024	J	`jnl`	SQL-PaLM: Improved large language model adaptation for Text-to-SQL. Trans. Mach. Learn. Res. Ruoxi Sun, Sercan Ö. Arik, Alexandre Muzio, Lesly Miculicich, Satya Kesav Gundabathula, Pengcheng Yin, Hanjun Dai, Hootan Nakhost, Rajarishi Sinha, Zifeng Wang, Tomas Pfister
2024	A*	`conf`	TYGR: Type Inference on Stripped Binaries using Graph Neural Networks. USENIX Security Symposium Chang Zhu, Ziyang Li, Anton Xue, Ati Priya Bajaj, Wil Gibbs, Yibo Liu, Rajeev Alur, Tiffany Bao, Hanjun Dai, Adam Doupé, Mayur Naik, Yan Shoshitaishvili, Ruoyu Wang, Aravind Machiry
2024	A*	`conf`	UQE: A Query Engine for Unstructured Databases. NeurIPS Hanjun Dai, Bethany Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans
2024	J	`jnl`	UQE: A Query Engine for Unstructured Databases. CoRR Hanjun Dai, Bethany Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans
2024	J	`jnl`	Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF. CoRR Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai
2023	A*	`conf`	Any-scale Balanced Samplers for Discrete Space. ICLR Haoran Sun, Bo Dai, Charles Sutton, Dale Schuurmans, Hanjun Dai
2023	—	`conf`	Better Zero-Shot Reasoning with Self-Adaptive Prompting. ACL (Findings) Xingchen Wan, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arik, Tomas Pfister
2023	J	`jnl`	Better Zero-Shot Reasoning with Self-Adaptive Prompting. CoRR Xingchen Wan, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arik, Tomas Pfister
2023	A*	`conf`	DISCS: A Benchmark for Discrete Sampling. NeurIPS Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai
2023	A	`conf`	Discrete Langevin Samplers via Wasserstein Gradient Flow. AISTATS Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans
2023	J	`jnl`	Document Entity Retrieval with Massive and Noisy Pre-training. CoRR Lijun Yu, Jin Miao, Xiaoyu Sun, Jiayi Chen, Alexander G. Hauptmann, Hanjun Dai, Wei Wei
2023	—	`conf`	DocumentNet: Bridging the Data Gap in Document Pre-training. EMNLP (Industry Track) Lijun Yu, Jin Miao, Xiaoyu Sun, Jiayi Chen, Alexander G. Hauptmann, Hanjun Dai, Wei Wei
2023	A*	`conf`	Gradient-Free Structured Pruning with Unlabeled Data. ICML Azade Nova, Hanjun Dai, Dale Schuurmans
2023	J	`jnl`	Gradient-Free Structured Pruning with Unlabeled Data. CoRR Azade Nova, Hanjun Dai, Dale Schuurmans
2023	A*	`conf`	LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. NeurIPS Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
2023	J	`jnl`	LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. CoRR Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
2023	J	`jnl`	Large Language Models can Learn Rules. CoRR Zhaocheng Zhu, Yuan Xue, Xinyun Chen, Denny Zhou, Jian Tang, Dale Schuurmans, Hanjun Dai
2023	A*	`conf`	Learning Universal Policies via Text-Guided Video Generation. NeurIPS Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Josh Tenenbaum, Dale Schuurmans, Pieter Abbeel
2023	J	`jnl`	Learning Universal Policies via Text-Guided Video Generation. CoRR Yilun Du, Mengjiao Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, Pieter Abbeel
2023	A	`conf`	Learning to Optimize with Stochastic Dominance Constraints. AISTATS Hanjun Dai, Yuan Xue, Niao He, Yixin Wang, Na Li, Dale Schuurmans, Bo Dai
2023	J	`jnl`	Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets. CoRR Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
2023	A*	`conf`	Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets. NeurIPS Dinghuai Zhang, Hanjun Dai, Nikolay Malkin, Aaron C. Courville, Yoshua Bengio, Ling Pan
2023	—	`conf`	On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval. EMNLP (Findings) Jiayi Chen, Hanjun Dai, Bo Dai, Aidong Zhang, Wei Wei
2023	J	`jnl`	On Task-personalized Multimodal Few-shot Learning for Visually-rich Document Entity Retrieval. CoRR Jiayi Chen, Hanjun Dai, Bo Dai, Aidong Zhang, Wei Wei
2023	A*	`conf`	Revisiting Sampling for Combinatorial Optimization. ICML Haoran Sun, Katayoon Goshvadi, Azade Nova, Dale Schuurmans, Hanjun Dai
2023	J	`jnl`	SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL. CoRR Ruoxi Sun, Sercan Ö. Arik, Hootan Nakhost, Hanjun Dai, Rajarishi Sinha, Pengcheng Yin, Tomas Pfister
2023	—	`conf`	SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data. EMNLP (Findings) Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister
2023	J	`jnl`	SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data. CoRR Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister
2023	A*	`conf`	Score-based Continuous-time Discrete Diffusion Models. ICLR Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai
2023	A*	`conf`	Universal Self-Adaptive Prompting. EMNLP Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Eisenschlos, Sercan Ö. Arik, Tomas Pfister
2023	J	`jnl`	Universal Self-adaptive Prompting. CoRR Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Martin Eisenschlos, Sercan Ö. Arik, Tomas Pfister
2023	A*	`conf`	Video Timeline Modeling For News Story Understanding. NeurIPS Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong
2023	J	`jnl`	Video Timeline Modeling For News Story Understanding. CoRR Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong
2022	J	`jnl`	Annealed Training for Combinatorial Optimization on Graphs. CoRR Haoran Sun, Etash Kumar Guha, Hanjun Dai
2022	A*	`conf`	CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation. ICLR Pardis Pashakhanloo, Aaditya Naik, Yuepeng Wang, Hanjun Dai, Petros Maniatis, Mayur Naik
2022	A*	`conf`	CrossBeam: Learning to Search in Bottom-Up Program Synthesis. ICLR Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton
2022	J	`jnl`	CrossBeam: Learning to Search in Bottom-Up Program Synthesis. CoRR Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton
2022	J	`jnl`	Discrete Langevin Sampler via Wasserstein Gradient Flow. CoRR Haoran Sun, Hanjun Dai, Bo Dai, Haomin Zhou, Dale Schuurmans
2022	A*	`conf`	Does GNN Pretraining Help Molecular Representation? NeurIPS Ruoxi Sun, Hanjun Dai, Adams Wei Yu
2022	J	`jnl`	Does GNN Pretraining Help Molecular Representation? CoRR Ruoxi Sun, Hanjun Dai, Adams Wei Yu
2022	J	`jnl`	Learning to Optimize with Stochastic Dominance Constraints. CoRR Hanjun Dai, Yuan Xue, Niao He, Bethany Wang, Na Li, Dale Schuurmans, Bo Dai
2022	A*	`conf`	Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization. ICML Hanjun Dai, Mengjiao Yang, Yuan Xue, Dale Schuurmans, Bo Dai
2022	A*	`conf`	Neural Stochastic Dual Dynamic Programming. ICLR Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai
2022	A*	`conf`	Optimal Scaling for Locally Balanced Proposals in Discrete Spaces. NeurIPS Haoran Sun, Hanjun Dai, Dale Schuurmans
2022	J	`jnl`	Optimal Scaling for Locally Balanced Proposals in Discrete Spaces. CoRR Haoran Sun, Hanjun Dai, Dale Schuurmans
2022	A*	`conf`	Path Auxiliary Proposal for MCMC in Discrete Space. ICLR Haoran Sun, Hanjun Dai, Wei Xia, Arun Ramamurthy
2022	A*	`conf`	SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs. KDD Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans
2022	J	`jnl`	Score-based Continuous-time Discrete Diffusion Models. CoRR Haoran Sun, Lijun Yu, Bo Dai, Dale Schuurmans, Hanjun Dai
2021	A*	`conf`	BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration. ICLR Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton, Hanjun Dai
2021	A*	`conf`	Combiner: Full Attention Transformer with Sparse Computation Cost. NeurIPS Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai
2021	J	`jnl`	Combiner: Full Attention Transformer with Sparse Computation Cost. CoRR Hongyu Ren, Hanjun Dai, Zihang Dai, Mengjiao Yang, Jure Leskovec, Dale Schuurmans, Bo Dai
2021	A*	`conf`	LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs. ICML Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou
2021	A*	`conf`	Molecule Optimization by Explainable Evolution. ICLR Binghong Chen, Tianzhe Wang, Chengtao Li, Hanjun Dai, Le Song
2021	J	`jnl`	Neural Stochastic Dual Dynamic Programming. CoRR Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai
2021	J	`jnl`	SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs. CoRR Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Denny Zhou, Jure Leskovec, Dale Schuurmans
2021	A*	`conf`	SpreadsheetCoder: Formula Prediction from Semi-structured Context. ICML Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou
2021	J	`jnl`	SpreadsheetCoder: Formula Prediction from Semi-structured Context. CoRR Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou
2021	A*	`conf`	Towards understanding retrosynthesis by energy-based models. NeurIPS Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai
2020	—	`conf`	Code2Inv: A Deep Learning Framework for Program Verification. CAV (2) Xujie Si, Aaditya Naik, Hanjun Dai, Mayur Naik, Le Song
2020	J	`jnl`	Differentiable Top-k Operator with Optimal Transport. CoRR Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
2020	A*	`conf`	Differentiable Top-k with Optimal Transport. NeurIPS Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
2020	A*	`conf`	Energy-Based Processes for Exchangeable Data. ICML Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
2020	J	`jnl`	Energy-Based Processes for Exchangeable Data. CoRR Mengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans
2020	J	`jnl`	Energy-based View of Retrosynthesis. CoRR Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai
2020	A*	`conf`	Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs. ICLR Elizabeth Dinella, Hanjun Dai, Ziyang Li, Mayur Naik, Le Song, Ke Wang
2020	A*	`conf`	Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. NeurIPS Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans
2020	J	`jnl`	Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. CoRR Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans
2020	—	`—`	Learning Neural Algorithms with Graph Structures. Hanjun Dai
2020	A*	`conf`	Learning To Stop While Learning To Predict. ICML Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song
2020	J	`jnl`	Learning to Stop While Learning to Predict. CoRR Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song
2020	J	`jnl`	Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders. CoRR Rohit Batra, Hanjun Dai, Tran Doan Huan, Lihua Chen, Chiho Kim, Will R. Gutekunst, Le Song, Rampi Ramprasad
2020	A*	`conf`	Retro: Learning Retrosynthetic Planning with Neural Guided A Search. ICML Binghong Chen, Chengtao Li, Hanjun Dai, Le Song
2020	J	`jnl`	Retro: Learning Retrosynthetic Planning with Neural Guided A Search. CoRR Binghong Chen, Chengtao Li, Hanjun Dai, Le Song
2020	J	`jnl`	Retrosynthesis Prediction with Conditional Graph Logic Network. CoRR Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song
2020	A*	`conf`	Scalable Deep Generative Modeling for Sparse Graphs. ICML Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans
2020	J	`jnl`	Scalable Deep Generative Modeling for Sparse Graphs. CoRR Hanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans
2019	A*	`conf`	CompILE: Compositional Imitation Learning and Execution. ICML Thomas Kipf, Yujia Li, Hanjun Dai, Vinícius Flores Zambaldi, Alvaro Sanchez-Gonzalez, Edward Grefenstette, Pushmeet Kohli, Peter W. Battaglia
2019	J	`jnl`	Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification. CoRR Harsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru
2019	A*	`conf`	Exponential Family Estimation via Adversarial Dynamics Embedding. NeurIPS Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans
2019	J	`jnl`	Exponential Family Estimation via Adversarial Dynamics Embedding. CoRR Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans
2019	A	`conf`	Kernel Exponential Family Estimation via Doubly Dual Embedding. AISTATS Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He
2019	A*	`conf`	Learning Transferable Graph Exploration. NeurIPS Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli
2019	J	`jnl`	Learning Transferable Graph Exploration. CoRR Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli
2019	—	`conf`	Learning a Meta-Solver for Syntax-Guided Program Synthesis. ICLR (Poster) Xujie Si, Yuan Yang, Hanjun Dai, Mayur Naik, Le Song
2019	J	`jnl`	Meta Particle Flow for Sequential Bayesian Inference. CoRR Xinshi Chen, Hanjun Dai, Le Song
2019	A*	`conf`	Particle Flow Bayes' Rule. ICML Xinshi Chen, Hanjun Dai, Le Song
2019	A*	`conf`	Retrosynthesis Prediction with Conditional Graph Logic Network. NeurIPS Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song
2018	—	`conf`	Additive Margin Softmax for Face Verification. ICLR (Workshop) Feng Wang, Weiyang Liu, Hanjun Dai, Haijun Liu, Jian Cheng
2018	A*	`conf`	Adversarial Attack on Graph Structured Data. ICML Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song
2018	J	`jnl`	Adversarial Attack on Graph Structured Data. CoRR Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, Le Song
2018	J	`jnl`	Compositional Imitation Learning: Explaining and executing one task at a time. CoRR Thomas Kipf, Yujia Li, Hanjun Dai, Vinícius Flores Zambaldi, Edward Grefenstette, Pushmeet Kohli, Peter W. Battaglia
2018	A*	`conf`	Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification. NeurIPS Harsh Shrivastava, Eugene Bart, Bob Price, Hanjun Dai, Bo Dai, Srinivas Aluru
2018	A*	`conf`	Coupled Variational Bayes via Optimization Embedding. NeurIPS Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song
2018	J	`jnl`	KG^2: Learning to Reason Science Exam Questions with Contextual Knowledge Graph Embeddings. CoRR Yuyu Zhang, Hanjun Dai, Kamil Toraman, Le Song
2018	J	`jnl`	Kernel Exponential Family Estimation via Doubly Dual Embedding. CoRR Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He
2018	A*	`conf`	Learning Loop Invariants for Program Verification. NeurIPS Xujie Si, Hanjun Dai, Mukund Raghothaman, Mayur Naik, Le Song
2018	A*	`conf`	Learning Steady-States of Iterative Algorithms over Graphs. ICML Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alexander J. Smola, Le Song
2018	—	`conf`	Syntax-Directed Variational Autoencoder for Structured Data. ICLR (Poster) Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song
2018	J	`jnl`	Syntax-Directed Variational Autoencoder for Structured Data. CoRR Hanjun Dai, Yingtao Tian, Bo Dai, Steven Skiena, Le Song
2018	A*	`conf`	Variational Reasoning for Question Answering With Knowledge Graph. AAAI Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J. Smola, Le Song
2017	J	`jnl`	Know-Evolve: Deep Reasoning in Temporal Knowledge Graphs. CoRR Rakshit S. Trivedi, Hanjun Dai, Yichen Wang, Le Song
2017	A*	`conf`	Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs. ICML Rakshit S. Trivedi, Hanjun Dai, Yichen Wang, Le Song
2017	—	`conf`	Learning Combinatorial Optimization Algorithms over Graphs. NIPS Elias B. Khalil, Hanjun Dai, Yuyu Zhang, Bistra Dilkina, Le Song
2017	J	`jnl`	Learning Combinatorial Optimization Algorithms over Graphs. CoRR Hanjun Dai, Elias B. Khalil, Yuyu Zhang, Bistra Dilkina, Le Song
2017	—	`conf`	Recurrent Hidden Semi-Markov Model. ICLR (Poster) Hanjun Dai, Bo Dai, Yan-Ming Zhang, Shuang Li, Le Song
2017	J	`jnl`	Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape. Bioinform. Hanjun Dai, Ramzan Umarov, Hiroyuki Kuwahara, Yu Li, Le Song, Xin Gao
2017	J	`jnl`	Variational Reasoning for Question Answering with Knowledge Graph. CoRR Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J. Smola, Le Song
2016	A*	`conf`	Discriminative Embeddings of Latent Variable Models for Structured Data. ICML Hanjun Dai, Bo Dai, Le Song
2016	J	`jnl`	Discriminative Embeddings of Latent Variable Models for Structured Data. CoRR Hanjun Dai, Bo Dai, Le Song
2016	A	`conf`	Provable Bayesian Inference via Particle Mirror Descent. AISTATS Bo Dai, Niao He, Hanjun Dai, Le Song
2016	J	`jnl`	Recurrent Coevolutionary Feature Embedding Processes for Recommendation. CoRR Hanjun Dai, Yichen Wang, Rakshit S. Trivedi, Le Song
2016	—	`conf`	Recurrent Coevolutionary Latent Feature Processes for Continuous-Time Recommendation. DLRS@RecSys Hanjun Dai, Yichen Wang, Rakshit S. Trivedi, Le Song
2016	A*	`conf`	Recurrent Marked Temporal Point Processes: Embedding Event History to Vector. KDD Nan Du, Hanjun Dai, Rakshit S. Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, Le Song
2015	J	`jnl`	KNET: A General Framework for Learning Word Embedding Using Morphological Knowledge. ACM Trans. Inf. Syst. Qing Cui, Bin Gao, Jiang Bian, Siyu Qiu, Hanjun Dai, Tie-Yan Liu
2015	—	`conf`	M-Statistic for Kernel Change-Point Detection. NIPS Shuang Li, Yao Xie, Hanjun Dai, Le Song
2015	J	`jnl`	M-Statistic for Kernel Change-Point Detection. CoRR Shuang Li, Yao Xie, Hanjun Dai, Le Song
2015	J	`jnl`	Online Supervised Subspace Tracking. CoRR Yao Xie, Ruiyang Song, Hanjun Dai, Qingbin Li, Le Song
2015	J	`jnl`	Scalable Bayesian Inference via Particle Mirror Descent. CoRR Bo Dai, Niao He, Hanjun Dai, Le Song
2014	B	`conf`	A Probabilistic Model for Learning Multi-Prototype Word Embeddings. COLING Fei Tian, Hanjun Dai, Jiang Bian, Bin Gao, Rui Zhang, Enhong Chen, Tie-Yan Liu
2014	A*	`conf`	Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. AAAI Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu
2014	J	`jnl`	Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks. CoRR Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, Tie-Yan Liu