Zhenwen Dai - RankMe

57 papers A* 14A 7B 1Journal 28Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Learning Optimal Personalised Reservation Prices in Impression Ad Auctions with Mixture Density Networks. CIKM Dmitrii Moor, Emma Zetterdahl, Paul van Vliet, Zhenwen Dai, Mounia Lalmas
2025	—	`conf`	Optimising Budget Management via Primal-Dual Approximation with Constrained Polynomial Weights Update. KDD (2) Dmitrii Moor, Per Berglund, Hannes Karlbom, Zhenwen Dai, Kyle Kretschman, Mounia Lalmas
2025	A	`conf`	Prompt-to-Slate: Diffusion Models for Prompt-Conditioned Slate Generation. RecSys Federico Tomasi, Francesco Fabbri, Justin Carter, Elias Kalomiris, Mounia Lalmas, Zhenwen Dai
2024	J	`jnl`	Diffusion Model for Slate Recommendation. CoRR Federico Tomasi, Francesco Fabbri, Mounia Lalmas, Zhenwen Dai
2024	A*	`conf`	In-context Exploration-Exploitation for Reinforcement Learning. ICLR Zhenwen Dai, Federico Tomasi, Sina Ghiassian
2024	J	`jnl`	In-context Exploration-Exploitation for Reinforcement Learning. CoRR Zhenwen Dai, Federico Tomasi, Sina Ghiassian
2023	J	`jnl`	A Strong Baseline for Batch Imitation Learning. CoRR Matthew Smith, Lucas Maystre, Zhenwen Dai, Kamil Ciosek
2023	A*	`conf`	Automatic Music Playlist Generation via Simulation-based Reinforcement Learning. KDD Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai
2023	J	`jnl`	Automatic Music Playlist Generation via Simulation-based Reinforcement Learning. CoRR Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai
2023	A	`conf`	Exploiting Sequential Music Preferences via Optimisation-Based Sequencing. CIKM Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas
2023	J	`jnl`	Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics. CoRR Mu Niu, Zhenwen Dai, Pokman Cheung, Yizhu Wang
2023	J	`jnl`	Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics. J. Mach. Learn. Res. Mu Niu, Zhenwen Dai, Pokman Cheung, Yizhu Wang
2023	A	`conf`	The ELBO of Variational Autoencoders Converges to a Sum of Entropies. AISTATS Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke
2022	A	`conf`	Efficient inference for dynamic topic modeling with large vocabularies. UAI Federico Tomasi, Mounia Lalmas, Zhenwen Dai
2021	A*	`conf`	Black-box density function estimation using recursive partitioning. ICML Erik Bodin, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek
2021	J	`jnl`	Making Differentiable Architecture Search less local. CoRR Erik Bodin, Federico Tomasi, Zhenwen Dai
2021	J	`jnl`	Model Selection for Production System via Automated Online Experiments. CoRR Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Ben Carterette, Mounia Lalmas-Roelleke
2020	J	`jnl`	Black-box density function estimation using recursive partitioning. CoRR Erik Bodin, Zhenwen Dai, Neill D. F. Campbell, Carl Henrik Ek
2020	J	`jnl`	Data-Driven Mode Identification and Unsupervised Fault Detection for Nonlinear Multimode Processes. IEEE Trans. Ind. Informatics Bei Wang, Zhichao Li, Zhenwen Dai, Neil D. Lawrence, Xuefeng Yan
2020	A*	`conf`	Model Selection for Production System via Automated Online Experiments. NeurIPS Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Benjamin A. Carterette, Mounia Lalmas
2020	A*	`conf`	Modulating Surrogates for Bayesian Optimization. ICML Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek
2020	A	`conf`	Stochastic Variational Inference for Dynamic Correlated Topic Models. UAI Federico Tomasi, Praveen Chandar, Gal Levy-Fix, Mounia Lalmas-Roelleke, Zhenwen Dai
2020	J	`jnl`	The Evidence Lower Bound of Variational Autoencoders Converges to a Sum of Three Entropies. CoRR Jörg Lücke, Dennis Forster, Zhenwen Dai
2019	J	`jnl`	A probabilistic principal component analysis-based approach in process monitoring and fault diagnosis with application in wastewater treatment plant. Appl. Soft Comput. Bei Wang, Zhichao Li, Zhenwen Dai, Neil D. Lawrence, Xuefeng Yan
2019	A*	`conf`	Meta-Surrogate Benchmarking for Hyperparameter Optimization. NeurIPS Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier González
2019	J	`jnl`	Meta-Surrogate Benchmarking for Hyperparameter Optimization. CoRR Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier González
2019	J	`jnl`	ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions. CoRR Georgios Exarchakis, Jörg Bornschein, Abdul-Saboor Sheikh, Zhenwen Dai, Marc Henniges, Jakob Drefs, Jörg Lücke
2019	J	`jnl`	STRFs in primary auditory cortex emerge from masking-based statistics of natural sounds. PLoS Comput. Biol. Abdul-Saboor Sheikh, Nicol S. Harper, Jakob Drefs, Yosef Singer, Zhenwen Dai, Richard E. Turner, Jörg Lücke
2019	A*	`conf`	Variational Information Distillation for Knowledge Transfer. CVPR Sungsoo Ahn, Shell Xu Hu, Andreas C. Damianou, Neil D. Lawrence, Zhenwen Dai
2019	J	`jnl`	Variational Information Distillation for Knowledge Transfer. CoRR Sungsoo Ahn, Shell Xu Hu, Andreas C. Damianou, Neil D. Lawrence, Zhenwen Dai
2018	J	`jnl`	Intrinsic Gaussian processes on complex constrained domains. CoRR Mu Niu, Pokman Cheung, Lizhen Lin, Zhenwen Dai, Neil D. Lawrence, David B. Dunson
2018	A*	`conf`	Structured Variationally Auto-encoded Optimization. ICML Xiaoyu Lu, Javier González, Zhenwen Dai, Neil D. Lawrence
2018	—	`conf`	Truncated Variational Sampling for 'Black Box' Optimization of Generative Models. LVA/ICA Jörg Lücke, Zhenwen Dai, Georgios Exarchakis
2017	J	`jnl`	Auto-Differentiating Linear Algebra. CoRR Matthias W. Seeger, Asmus Hetzel, Zhenwen Dai, Neil D. Lawrence
2017	—	`conf`	Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. NIPS Zhenwen Dai, Mauricio A. Álvarez, Neil D. Lawrence
2017	J	`jnl`	Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. CoRR Zhenwen Dai, Mauricio A. Álvarez, Neil D. Lawrence
2017	J	`jnl`	Efficient inference for sparse latent variable models of transcriptional regulation. Bioinform. Zhenwen Dai, Mudassar Iqbal, Neil D. Lawrence, Magnus Rattray
2017	J	`jnl`	GP-Select: Accelerating EM Using Adaptive Subspace Preselection. Neural Comput. Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton
2017	A*	`conf`	Preferential Bayesian Optimization. ICML Javier González, Zhenwen Dai, Andreas C. Damianou, Neil D. Lawrence
2016	A	`conf`	Batch Bayesian Optimization via Local Penalization. AISTATS Javier González, Zhenwen Dai, Philipp Hennig, Neil D. Lawrence
2016	J	`jnl`	Data-Driven Detection of Prominent Objects. IEEE Trans. Pattern Anal. Mach. Intell. José A. Rodríguez-Serrano, Diane Larlus, Zhenwen Dai
2016	A*	`conf`	Recurrent Gaussian Processes. ICLR (Poster) César Lincoln C. Mattos, Zhenwen Dai, Andreas C. Damianou, Jeremy Forth, Guilherme A. Barreto, Neil D. Lawrence
2016	J	`jnl`	Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model. CoRR Fariba Yousefi, Zhenwen Dai, Carl Henrik Ek, Neil D. Lawrence
2016	A*	`conf`	Variational Auto-encoded Deep Gaussian Processes. ICLR (Poster) Zhenwen Dai, Andreas C. Damianou, Javier González, Neil D. Lawrence
2015	J	`jnl`	Spike and Slab Gaussian Process Latent Variable Models. CoRR Zhenwen Dai, James Hensman, Neil D. Lawrence
2014	J	`jnl`	Autonomous Document Cleaning - A Generative Approach to Reconstruct Strongly Corrupted Scanned Texts. IEEE Trans. Pattern Anal. Mach. Intell. Zhenwen Dai, Jörg Lücke
2014	J	`jnl`	GP-select: Accelerating EM using adaptive subspace preselection. CoRR Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton
2014	J	`jnl`	Gaussian Process Models with Parallelization and GPU acceleration. CoRR Zhenwen Dai, Andreas C. Damianou, James Hensman, Neil D. Lawrence
2013	—	`—`	Unsupervised learning of invariant object representations: a probabilistic generative modeling approach. Zhenwen Dai
2013	—	`conf`	What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach. NIPS Zhenwen Dai, Georgios Exarchakis, Jörg Lücke
2012	J	`jnl`	Autonomous Cleaning of Corrupted Scanned Documents - A Generative Modeling Approach CoRR Zhenwen Dai, Jörg Lücke
2012	A*	`conf`	Autonomous cleaning of corrupted scanned documents - A generative modeling approach. CVPR Zhenwen Dai, Jörg Lücke
2012	A*	`conf`	Unsupervised learning of translation invariant occlusive components. CVPR Zhenwen Dai, Jörg Lücke
2011	A*	`conf`	Pose estimation from reflections for specular surface recovery. ICCV Miaomiao Liu, Kwan-Yee Kenneth Wong, Zhenwen Dai, Zhihu Chen
2010	—	`conf`	Specular Surface Recovery from Reflections of a Planar Pattern Undergoing an Unknown Pure Translation. ACCV (2) Miaomiao Liu, Kwan-Yee Kenneth Wong, Zhenwen Dai, Zhihu Chen
2009	—	`conf`	Polygonal Light Source Estimation. ACCV (3) Dirk Schnieders, Kwan-Yee Kenneth Wong, Zhenwen Dai
2007	B	`conf`	Understanding Research Field Evolving and Trend with Dynamic Bayesian Networks. PAKDD Jinlong Wang, Congfu Xu, Gang Li, Zhenwen Dai, Guojing Luo