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2020 – today
- 2024
[c25]Zhenwen Dai, Federico Tomasi, Sina Ghiassian:
In-context Exploration-Exploitation for Reinforcement Learning. ICLR 2024- [i20]Zhenwen Dai, Federico Tomasi, Sina Ghiassian:
In-context Exploration-Exploitation for Reinforcement Learning. CoRR abs/2403.06826 (2024) - [i19]Federico Tomasi, Francesco Fabbri, Mounia Lalmas, Zhenwen Dai:
Diffusion Model for Slate Recommendation. CoRR abs/2408.06883 (2024) - 2023
- [j8]Mu Niu, Zhenwen Dai, Pokman Cheung, Yizhu Wang:
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics. J. Mach. Learn. Res. 24: 104:1-104:42 (2023) - [c24]Simon Damm
, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke:
The ELBO of Variational Autoencoders Converges to a Sum of Entropies. AISTATS 2023: 3931-3960 - [c23]Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas:
Exploiting Sequential Music Preferences via Optimisation-Based Sequencing. CIKM 2023: 4759-4765 - [c22]Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai:
Automatic Music Playlist Generation via Simulation-based Reinforcement Learning. KDD 2023: 4948-4957 - [i18]Mu Niu, Zhenwen Dai, Pokman Cheung, Yizhu Wang:
Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics. CoRR abs/2301.06533 (2023) - [i17]Matthew Smith, Lucas Maystre, Zhenwen Dai, Kamil Ciosek:
A Strong Baseline for Batch Imitation Learning. CoRR abs/2302.02788 (2023) - [i16]Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai:
Automatic Music Playlist Generation via Simulation-based Reinforcement Learning. CoRR abs/2310.09123 (2023) - 2022
- [c21]Federico Tomasi, Mounia Lalmas, Zhenwen Dai:
Efficient inference for dynamic topic modeling with large vocabularies. UAI 2022: 1950-1959 - 2021
- [c20]Erik Bodin, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek:
Black-box density function estimation using recursive partitioning. ICML 2021: 1015-1025 - [i15]Erik Bodin, Federico Tomasi, Zhenwen Dai:
Making Differentiable Architecture Search less local. CoRR abs/2104.10450 (2021) - [i14]Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Ben Carterette, Mounia Lalmas-Roelleke:
Model Selection for Production System via Automated Online Experiments. CoRR abs/2105.13420 (2021) - 2020
- [j7]Bei Wang, Zhichao Li, Zhenwen Dai, Neil D. Lawrence, Xuefeng Yan:
Data-Driven Mode Identification and Unsupervised Fault Detection for Nonlinear Multimode Processes. IEEE Trans. Ind. Informatics 16(6): 3651-3661 (2020) - [c19]Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek:
Modulating Surrogates for Bayesian Optimization. ICML 2020: 970-979 - [c18]Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Benjamin A. Carterette, Mounia Lalmas:
Model Selection for Production System via Automated Online Experiments. NeurIPS 2020 - [c17]Federico Tomasi, Praveen Chandar, Gal Levy-Fix, Mounia Lalmas-Roelleke, Zhenwen Dai:
Stochastic Variational Inference for Dynamic Correlated Topic Models. UAI 2020: 859-868 - [i13]Erik Bodin, Zhenwen Dai, Neill D. F. Campbell, Carl Henrik Ek:
Black-box density function estimation using recursive partitioning. CoRR abs/2010.13632 (2020) - [i12]Jörg Lücke, Dennis Forster, Zhenwen Dai:
The Evidence Lower Bound of Variational Autoencoders Converges to a Sum of Three Entropies. CoRR abs/2010.14860 (2020)
2010 – 2019
- 2019
- [j6]Bei Wang, Zhichao Li, Zhenwen Dai, Neil D. Lawrence, Xuefeng Yan:
A probabilistic principal component analysis-based approach in process monitoring and fault diagnosis with application in wastewater treatment plant. Appl. Soft Comput. 82 (2019) - [j5]Abdul-Saboor Sheikh, Nicol S. Harper, Jakob Drefs, Yosef Singer, Zhenwen Dai, Richard E. Turner, Jörg Lücke:
STRFs in primary auditory cortex emerge from masking-based statistics of natural sounds. PLoS Comput. Biol. 15(1) (2019) - [c16]Sungsoo Ahn, Shell Xu Hu, Andreas C. Damianou, Neil D. Lawrence, Zhenwen Dai:
Variational Information Distillation for Knowledge Transfer. CVPR 2019: 9163-9171 - [c15]Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier González:
Meta-Surrogate Benchmarking for Hyperparameter Optimization. NeurIPS 2019: 6267-6277 - [i11]Sungsoo Ahn, Shell Xu Hu, Andreas C. Damianou, Neil D. Lawrence, Zhenwen Dai:
Variational Information Distillation for Knowledge Transfer. CoRR abs/1904.05835 (2019) - [i10]Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier González:
Meta-Surrogate Benchmarking for Hyperparameter Optimization. CoRR abs/1905.12982 (2019) - [i9]Georgios Exarchakis, Jörg Bornschein, Abdul-Saboor Sheikh, Zhenwen Dai, Marc Henniges, Jakob Drefs, Jörg Lücke:
ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions. CoRR abs/1908.06843 (2019) - 2018
- [c14]Jörg Lücke, Zhenwen Dai, Georgios Exarchakis:
Truncated Variational Sampling for 'Black Box' Optimization of Generative Models. LVA/ICA 2018: 467-478 - [c13]Xiaoyu Lu, Javier González, Zhenwen Dai, Neil D. Lawrence:
Structured Variationally Auto-encoded Optimization. ICML 2018: 3273-3281 - [i8]Mu Niu, Pokman Cheung, Lizhen Lin, Zhenwen Dai, Neil D. Lawrence, David B. Dunson:
Intrinsic Gaussian processes on complex constrained domains. CoRR abs/1801.01061 (2018) - 2017
- [j4]Zhenwen Dai, Mudassar Iqbal, Neil D. Lawrence, Magnus Rattray:
Efficient inference for sparse latent variable models of transcriptional regulation. Bioinform. 33(23): 3776-3783 (2017) - [j3]Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton:
GP-Select: Accelerating EM Using Adaptive Subspace Preselection. Neural Comput. 29(8): 2177-2202 (2017) - [c12]Javier González, Zhenwen Dai, Andreas C. Damianou, Neil D. Lawrence:
Preferential Bayesian Optimization. ICML 2017: 1282-1291 - [c11]Zhenwen Dai, Mauricio A. Álvarez, Neil D. Lawrence:
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. NIPS 2017: 5131-5139 - [i7]Zhenwen Dai, Mauricio A. Álvarez, Neil D. Lawrence:
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. CoRR abs/1705.09862 (2017) - [i6]Matthias W. Seeger, Asmus Hetzel, Zhenwen Dai, Neil D. Lawrence:
Auto-Differentiating Linear Algebra. CoRR abs/1710.08717 (2017) - 2016
- [j2]José A. Rodríguez-Serrano, Diane Larlus, Zhenwen Dai:
Data-Driven Detection of Prominent Objects. IEEE Trans. Pattern Anal. Mach. Intell. 38(10): 1969-1982 (2016) - [c10]Javier González, Zhenwen Dai, Philipp Hennig, Neil D. Lawrence:
Batch Bayesian Optimization via Local Penalization. AISTATS 2016: 648-657 - [c9]Zhenwen Dai, Andreas C. Damianou, Javier González, Neil D. Lawrence:
Variational Auto-encoded Deep Gaussian Processes. ICLR (Poster) 2016 - [c8]César Lincoln C. Mattos, Zhenwen Dai, Andreas C. Damianou, Jeremy Forth, Guilherme A. Barreto, Neil D. Lawrence:
Recurrent Gaussian Processes. ICLR (Poster) 2016 - [i5]Fariba Yousefi, Zhenwen Dai, Carl Henrik Ek, Neil D. Lawrence:
Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model. CoRR abs/1607.00067 (2016) - 2015
- [i4]Zhenwen Dai, James Hensman, Neil D. Lawrence:
Spike and Slab Gaussian Process Latent Variable Models. CoRR abs/1505.02434 (2015) - 2014
- [j1]Zhenwen Dai, Jörg Lücke:
Autonomous Document Cleaning - A Generative Approach to Reconstruct Strongly Corrupted Scanned Texts. IEEE Trans. Pattern Anal. Mach. Intell. 36(10): 1950-1962 (2014) - [i3]Zhenwen Dai, Andreas C. Damianou, James Hensman, Neil D. Lawrence:
Gaussian Process Models with Parallelization and GPU acceleration. CoRR abs/1410.4984 (2014) - [i2]Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton:
GP-select: Accelerating EM using adaptive subspace preselection. CoRR abs/1412.3411 (2014) - 2013
- [b1]Zhenwen Dai:
Unsupervised learning of invariant object representations: a probabilistic generative modeling approach. Goethe University Frankfurt am Main, 2013, pp. 1-130 - [c7]Zhenwen Dai, Georgios Exarchakis, Jörg Lücke:
What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach. NIPS 2013: 243-251 - 2012
- [c6]Zhenwen Dai, Jörg Lücke:
Unsupervised learning of translation invariant occlusive components. CVPR 2012: 2400-2407 - [c5]Zhenwen Dai, Jörg Lücke:
Autonomous cleaning of corrupted scanned documents - A generative modeling approach. CVPR 2012: 3338-3345 - [i1]Zhenwen Dai, Jörg Lücke:
Autonomous Cleaning of Corrupted Scanned Documents - A Generative Modeling Approach. CoRR abs/1201.2605 (2012) - 2011
- [c4]Miaomiao Liu, Kwan-Yee Kenneth Wong, Zhenwen Dai, Zhihu Chen:
Pose estimation from reflections for specular surface recovery. ICCV 2011: 579-586 - 2010
- [c3]Miaomiao Liu, Kwan-Yee Kenneth Wong, Zhenwen Dai, Zhihu Chen:
Specular Surface Recovery from Reflections of a Planar Pattern Undergoing an Unknown Pure Translation. ACCV (2) 2010: 137-147
2000 – 2009
- 2009
- [c2]Dirk Schnieders, Kwan-Yee Kenneth Wong, Zhenwen Dai:
Polygonal Light Source Estimation. ACCV (3) 2009: 96-107 - 2007
- [c1]Jinlong Wang, Congfu Xu, Gang Li, Zhenwen Dai, Guojing Luo:
Understanding Research Field Evolving and Trend with Dynamic Bayesian Networks. PAKDD 2007: 320-331
Coauthor Index
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last updated on 2024-10-07 22:24 CEST by the dblp team
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