Nevin Lianwen Zhang

Affiliations:
  • Hong Kong University of Science and Technology


According to our database1, Nevin Lianwen Zhang authored at least 99 papers between 1992 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2021
DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Handling Collocations in Hierarchical Latent Tree Analysis for Topic Modeling.
CoRR, 2020

Learning the Structure of Auto-Encoding Recommenders.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Response-Anticipated Memory for On-Demand Knowledge Integration in Response Generation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Not All Attention Is Needed: Gated Attention Network for Sequence Data.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Cleaned Similarity for Better Memory-Based Recommenders.
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering.
Proceedings of the 7th International Conference on Learning Representations, 2019

Modeling Multidimensional User Preferences for Collaborative Filtering.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Fast Structure Learning for Deep Feedforward Networks via Tree Skeleton Expansion.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2019

A Novel Document Generation Process for Topic Detection Based on Hierarchical Latent Tree Models.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2019

Conformative Filtering for Implicit Feedback Data.
Proceedings of the Advances in Information Retrieval, 2019

Learning to Abstract for Memory-augmented Conversational Response Generation.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
UC-LTM: Unidimensional clustering using latent tree models for discrete data.
Int. J. Approx. Reason., 2018

Using Taste Groups for Collaborative Filtering.
CoRR, 2018

Matrix Factorization Equals Efficient Co-occurrence Representation.
CoRR, 2018

Learning Hierarchical Item Categories from Implicit Feedback Data for Efficient Recommendations and Browsing.
CoRR, 2018

Learning Sparse Deep Feedforward Networks via Tree Skeleton Expansion.
CoRR, 2018

Latent Tree Variational Autoencoder for Joint Representation Learning and Multidimensional Clustering.
CoRR, 2018

Building Sparse Deep Feedforward Networks using Tree Receptive Fields.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017
Document Generation with Hierarchical Latent Tree Models.
CoRR, 2017

Conformative Filtering for Implicit Feedback Data.
CoRR, 2017

Latent tree models for hierarchical topic detection.
Artif. Intell., 2017

Mining Textual Reviews with Hierarchical Latent Tree Analysis.
Proceedings of the Data Mining and Big Data - Second International Conference, 2017

Topic Browsing System for Research Papers Based on Hierarchical Latent Tree Analysis.
Proceedings of the Web and Big Data - First International Joint Conference, 2017

Latent Tree Analysis.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Topic Browsing for Research Papers with Hierarchical Latent Tree Analysis.
CoRR, 2016

Identification and classification of TCM syndrome types among patients with vascular mild cognitive impairment using latent tree analysis.
CoRR, 2016

Latent Tree Models for Hierarchical Topic Detection.
CoRR, 2016

Progressive EM for Latent Tree Models and Hierarchical Topic Detection.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Greedy learning of latent tree models for multidimensional clustering.
Mach. Learn., 2015

Bayesian adaptive matrix factorization with automatic model selection.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Unidimensional Clustering of Discrete Data Using Latent Tree Models.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Latent tree models for rounding in spectral clustering.
Neurocomputing, 2014

An Evidence-Based Approach to Patient Classification in Traditional Chinese Medicine based on Latent Tree Analysis.
CoRR, 2014

Hierarchical Latent Tree Analysis for Topic Detection.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

A Study of Recently Discovered Equalities about Latent Tree Models Using Inverse Edges.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

2013
A Survey on Latent Tree Models and Applications.
J. Artif. Intell. Res., 2013

LTC: A latent tree approach to classification.
Int. J. Approx. Reason., 2013

Model-based clustering of high-dimensional data: Variable selection versus facet determination.
Int. J. Approx. Reason., 2013

Sidestepping the Triangulation Problem in Bayesian Net Computations
CoRR, 2013

Inter-causal Independence and Heterogeneous Factorization
CoRR, 2013

2012
Model-based multidimensional clustering of categorical data.
Artif. Intell., 2012

A Model-Based Approach to Rounding in Spectral Clustering.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

2011
Discovery of Regularities in the Use of Herbs in Traditional Chinese Medicine Prescriptions.
Proceedings of the New Frontiers in Applied Data Mining, 2011

Fast Multidimensional Clustering of Categorical Data.
Proceedings of the 2nd MultiClust Workshop: Discovering, 2011

Latent Tree Classifier.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2011

2010
The Role of Operation Granularity in Search-Based Learning of Latent Tree Models.
Proceedings of the New Frontiers in Artificial Intelligence, 2010

Variable Selection in Model-Based Clustering: To Do or To Facilitate.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Statistical truths in traditional Chinese medicine theories.
Proceedings of the 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, 2010

2008
Weights of Evidence and Internal Conflict for Support Functions.
Proceedings of the Classic Works of the Dempster-Shafer Theory of Belief Functions, 2008

Discovery of latent structures: Experience with the CoIL Challenge 2000 data set.
J. Syst. Sci. Complex., 2008

Latent Tree Models and Approximate Inference in Bayesian Networks.
J. Artif. Intell. Res., 2008

Latent tree models and diagnosis in traditional Chinese medicine.
Artif. Intell. Medicine, 2008

2007
Discovering Latent Structures: Experience with the CoIL Challenge 2000 Data Set.
Proceedings of the Computational Science - ICCS 2007, 7th International Conference, Beijing, China, May 27, 2007

Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine.
Proceedings of the Artificial Intelligence in Medicine, 2007

2006
Severity of Local Maxima for the EM Algorithm: Experiences with Hierarchical Latent Class Models.
Proceedings of the Third European Workshop on Probabilistic Graphical Models, 2006

Quartet-Based Learning of Shallow Latent Variables.
Proceedings of the Third European Workshop on Probabilistic Graphical Models, 2006

Quartet-Based Learning of Hierarchical Latent Class Models: Discovery of Shallow Latent Variables.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2006

2005
Restricted Value Iteration: Theory and Algorithms.
J. Artif. Intell. Res., 2005

Special Issue on ECSQARU-2003: The Seventh European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty: Message from the Guest Editors.
Int. J. Approx. Reason., 2005

Effective dimensions of partially observed polytrees.
Int. J. Approx. Reason., 2005

2004
Hierarchical Latent Class Models for Cluster Analysis.
J. Mach. Learn. Res., 2004

Effective Dimensions of Hierarchical Latent Class Models.
J. Artif. Intell. Res., 2004

Latent variable discovery in classification models.
Artif. Intell. Medicine, 2004

Efficient Learning of Hierarchical Latent Class Models.
Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2004), 2004

Reinforcement Learning in Episodic Non-stationary Markovian Environments.
Proceedings of the International Conference on Artificial Intelligence, 2004

2003
Exploiting Contextual Independence In Probabilistic Inference.
J. Artif. Intell. Res., 2003

Effective Dimensions of Partially Observed Polytrees.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2003

2002
Inference in Bayesian Networks: The Role of Context-Specific Independence.
Int. J. Inf. Technol. Decis. Mak., 2002

Dimension Correction for Hierarchical Latent Class Models.
Proceedings of the UAI '02, 2002

An Alternative Formulation of Dynamic-Programming Updates for POMDPs.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2002

Value Iteration Working with Belief Subset.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001
Speeding Up the Convergence of Value Iteration in Partially Observable Markov Decision Processes.
J. Artif. Intell. Res., 2001

Hidden-Mode Markov Decision Processes for Nonstationary Sequential Decision Making.
Proceedings of the Sequence Learning - Paradigms, Algorithms, and Applications, 2001

Space-Progressive Value Iteration: An Anytime Algorithm for a Class of POMDPs.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2001

Solving Hidden-Mode Markov Decision Problems.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

1999
A Method for Speeding Up Value Iteration in Partially Observable Markov Decision Processes.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

An Environment Model for Nonstationary Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

On the Role of Context-Specific Independence in Probabilistic Inference.
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

1998
Independence of causal influence and clique tree propagation.
Int. J. Approx. Reason., 1998

Probabilistic Inference in Influence Diagrams.
Comput. Intell., 1998

Computational Properties of Two Exact Algorithms for Bayesian Networks.
Appl. Intell., 1998

Planning with Partially Observable Markov Decision Processes: Advances in Exact Solution Method.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Context-Specific Independence, Decomposition of Conditional Probabilities, and Inference in Bayesian Networks.
Proceedings of the PRICAI'98, 1998

1997
A Model Approximation Scheme for Planning in Partially Observable Stochastic Domains.
J. Artif. Intell. Res., 1997

Fast Value Iteration for Goal-Directed Markov Decision Processes.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

Region-Based Approximations for Planning in Stochastic Domains.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

1996
Exploiting Causal Independence in Bayesian Network Inference.
J. Artif. Intell. Res., 1996

Irrelevance and ParameterLearning in Bayesian Networks.
Artif. Intell., 1996

1995
Inference with Causal Independence in the CPSC Network.
Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

1994
A computational theory of decision networks.
Int. J. Approx. Reason., 1994

Intercausal Independence and Heterogeneous Factorization.
Proceedings of the UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, 1994

Solving Asymmetric Decision Problems with Influence Diagrams.
Proceedings of the UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, 1994

1993
Incremental computation of the value of perfect information in stepwise-decomposable influence diagrams.
Proceedings of the UAI '93: Proceedings of the Ninth Annual Conference on Uncertainty in Artificial Intelligence, 1993

1992
Stepwise-Decomposable Influence Diagrams.
Proceedings of the 3rd International Conference on Principles of Knowledge Representation and Reasoning (KR'92). Cambridge, 1992


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