Probabilistic Latent Factor Model for Collaborative Filtering with Bayesian Inference
Jiansheng Fang,
Xiaoqing Zhang,
Yan Hu,
Yanwu Xu,
Ming Yang,
Jiang Liu
![Responsive image](/icpr/media/video_thumbnails/10831.jpg)
Auto-TLDR; Bayesian Latent Factor Model for Collaborative Filtering
Similar papers
Temporal Collaborative Filtering with Graph Convolutional Neural Networks
Esther Rodrigo-Bonet, Minh Duc Nguyen, Nikos Deligiannis
![Responsive image](/icpr/media/video_thumbnails/11432.jpg)
Auto-TLDR; Temporal Collaborative Filtering with Graph-Neural-Network-based Neural Networks
Abstract Slides Poster Similar
An Intransitivity Model for Matchup and Pairwise Comparison
Yan Gu, Jiuding Duan, Hisashi Kashima
![Responsive image](/icpr/media/video_thumbnails/10919.jpg)
Auto-TLDR; Blade-Chest: A Low-Rank Matrix Approach for Probabilistic Ranking of Players
Abstract Slides Poster Similar
Deep Topic Modeling by Multilayer Bootstrap Network and Lasso
![Responsive image](/icpr/media/video_thumbnails/11145.jpg)
Auto-TLDR; Unsupervised Deep Topic Modeling with Multilayer Bootstrap Network and Lasso
Abstract Slides Poster Similar
Aggregating Dependent Gaussian Experts in Local Approximation
![Responsive image](/icpr/media/video_thumbnails/11968.jpg)
Auto-TLDR; A novel approach for aggregating the Gaussian experts by detecting strong violations of conditional independence
Abstract Slides Poster Similar
Active Sampling for Pairwise Comparisons via Approximate Message Passing and Information Gain Maximization
Aliaksei Mikhailiuk, Clifford Wilmot, Maria Perez-Ortiz, Dingcheng Yue, Rafal Mantiuk
![Responsive image](/icpr/media/video_thumbnails/11157.jpg)
Auto-TLDR; ASAP: An Active Sampling Algorithm for Pairwise Comparison Data
Enhanced User Interest and Expertise Modeling for Expert Recommendation
Tongze He, Caili Guo, Yunfei Chu
![Responsive image](/icpr/media/video_thumbnails/10902.jpg)
Auto-TLDR; A Unified Framework for Expert Recommendation in Community Question Answering
Abstract Slides Poster Similar
Factor Screening Using Bayesian Active Learning and Gaussian Process Meta-Modelling
Cheng Li, Santu Rana, Andrew William Gill, Dang Nguyen, Sunil Kumar Gupta, Svetha Venkatesh
![Responsive image](/icpr/media/thumbnails/0981_FI.pdf.jpg)
Auto-TLDR; Data-Efficient Bayesian Active Learning for Factor Screening in Combat Simulations
Automatically Mining Relevant Variable Interactions Via Sparse Bayesian Learning
Ryoichiro Yafune, Daisuke Sakuma, Yasuo Tabei, Noritaka Saito, Hiroto Saigo
![Responsive image](/icpr/media/video_thumbnails/12047.jpg)
Auto-TLDR; Sparse Bayes for Interpretable Non-linear Prediction
Abstract Slides Poster Similar
Hierarchical Routing Mixture of Experts
Wenbo Zhao, Yang Gao, Shahan Ali Memon, Bhiksha Raj, Rita Singh
![Responsive image](/icpr/media/video_thumbnails/11832.jpg)
Auto-TLDR; A Binary Tree-structured Hierarchical Routing Mixture of Experts for Regression
Abstract Slides Poster Similar
Quantifying Model Uncertainty in Inverse Problems Via Bayesian Deep Gradient Descent
Riccardo Barbano, Chen Zhang, Simon Arridge, Bangti Jin
![Responsive image](/icpr/media/video_thumbnails/11008.jpg)
Auto-TLDR; Bayesian Neural Networks for Inverse Reconstruction via Bayesian Knowledge-Aided Computation
Abstract Slides Poster Similar
Variational Information Bottleneck Model for Accurate Indoor Position Recognition
![Responsive image](/icpr/media/video_thumbnails/11153.jpg)
Auto-TLDR; Variational Information Bottleneck for Indoor Positioning with WiFi Fingerprints
Abstract Slides Poster Similar
3CS Algorithm for Efficient Gaussian Process Model Retrieval
Fabian Berns, Kjeld Schmidt, Ingolf Bracht, Christian Beecks
![Responsive image](/icpr/media/video_thumbnails/11058.jpg)
Auto-TLDR; Efficient retrieval of Gaussian Process Models for large-scale data using divide-&-conquer-based approach
Abstract Slides Poster Similar
Epitomic Variational Graph Autoencoder
Rayyan Ahmad Khan, Muhammad Umer Anwaar, Martin Kleinsteuber
![Responsive image](/icpr/media/video_thumbnails/11744.jpg)
Auto-TLDR; EVGAE: A Generative Variational Autoencoder for Graph Data
Abstract Slides Poster Similar
Learning Parameter Distributions to Detect Concept Drift in Data Streams
Johannes Haug, Gjergji Kasneci
![Responsive image](/icpr/media/video_thumbnails/12023.jpg)
Auto-TLDR; A novel framework for the detection of concept drift in streaming environments
Abstract Slides Poster Similar
GPSRL: Learning Semi-Parametric Bayesian Survival Rule Lists from Heterogeneous Patient Data
Ameer Hamza Shakur, Xiaoning Qian, Zhangyang Wang, Bobak Mortazavi, Shuai Huang
![Responsive image](/icpr/media/video_thumbnails/12170.jpg)
Auto-TLDR; Semi-parametric Bayesian Survival Rule List Model for Heterogeneous Survival Data
Temporal Pattern Detection in Time-Varying Graphical Models
Federico Tomasi, Veronica Tozzo, Annalisa Barla
![Responsive image](/icpr/media/video_thumbnails/11399.jpg)
Auto-TLDR; A dynamical network inference model that leverages on kernels to consider general temporal patterns
Abstract Slides Poster Similar
Double Manifolds Regularized Non-Negative Matrix Factorization for Data Representation
Jipeng Guo, Shuai Yin, Yanfeng Sun, Yongli Hu
![Responsive image](/icpr/media/video_thumbnails/10944.jpg)
Auto-TLDR; Double Manifolds Regularized Non-negative Matrix Factorization for Clustering
Abstract Slides Poster Similar
Variational Deep Embedding Clustering by Augmented Mutual Information Maximization
Qiang Ji, Yanfeng Sun, Yongli Hu, Baocai Yin
![Responsive image](/icpr/media/video_thumbnails/11112.jpg)
Auto-TLDR; Clustering by Augmented Mutual Information maximization for Deep Embedding
Abstract Slides Poster Similar
Edge-Aware Graph Attention Network for Ratio of Edge-User Estimation in Mobile Networks
Jiehui Deng, Sheng Wan, Xiang Wang, Enmei Tu, Xiaolin Huang, Jie Yang, Chen Gong
![Responsive image](/icpr/media/video_thumbnails/12093.jpg)
Auto-TLDR; EAGAT: Edge-Aware Graph Attention Network for Automatic REU Estimation in Mobile Networks
Abstract Slides Poster Similar
Video Episode Boundary Detection with Joint Episode-Topic Model
Shunyao Wang, Ye Tian, Ruidong Wang, Yang Du, Han Yan, Ruilin Yang, Jian Ma
![Responsive image](/icpr/media/video_thumbnails/11094.jpg)
Auto-TLDR; Unsupervised Video Episode Boundary Detection for Bullet Screen Comment Video
Abstract Slides Poster Similar
Webly Supervised Image-Text Embedding with Noisy Tag Refinement
Niluthpol Mithun, Ravdeep Pasricha, Evangelos Papalexakis, Amit Roy-Chowdhury
![Responsive image](/icpr/media/video_thumbnails/11775.jpg)
Auto-TLDR; Robust Joint Embedding for Image-Text Retrieval Using Web Images
Feature-Aware Unsupervised Learning with Joint Variational Attention and Automatic Clustering
Wang Ru, Lin Li, Peipei Wang, Liu Peiyu
![Responsive image](/icpr/media/video_thumbnails/10947.jpg)
Auto-TLDR; Deep Variational Attention Encoder-Decoder for Clustering
Abstract Slides Poster Similar
Switching Dynamical Systems with Deep Neural Networks
Cesar Ali Ojeda Marin, Kostadin Cvejoski, Bogdan Georgiev, Ramses J. Sanchez
![Responsive image](/icpr/media/video_thumbnails/11629.jpg)
Auto-TLDR; Variational RNN for Switching Dynamics
Abstract Slides Poster Similar
Learning Sparse Deep Neural Networks Using Efficient Structured Projections on Convex Constraints for Green AI
Michel Barlaud, Frederic Guyard
![Responsive image](/icpr/media/thumbnails/0577_FI.pdf.jpg)
Auto-TLDR; Constrained Deep Neural Network with Constrained Splitting Projection
Abstract Slides Poster Similar
Deep Transformation Models: Tackling Complex Regression Problems with Neural Network Based Transformation Models
Beate Sick, Torsten Hothorn, Oliver Dürr
![Responsive image](/icpr/media/video_thumbnails/11146.jpg)
Auto-TLDR; A Deep Transformation Model for Probabilistic Regression
Abstract Slides Poster Similar
Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks
Denis Huseljic, Bernhard Sick, Marek Herde, Daniel Kottke
![Responsive image](/icpr/media/video_thumbnails/11987.jpg)
Auto-TLDR; AE-DNN: Modeling Uncertainty in Deep Neural Networks
Abstract Slides Poster Similar
An Empirical Bayes Approach to Topic Modeling
![Responsive image](/icpr/media/video_thumbnails/11188.png)
Auto-TLDR; An Empirical Bayes Based Framework for Topic Modeling in Documents
T-SVD Based Non-Convex Tensor Completion and Robust Principal Component Analysis
![Responsive image](/icpr/media/video_thumbnails/11716.jpg)
Auto-TLDR; Non-Convex tensor rank surrogate function and non-convex sparsity measure for tensor recovery
Abstract Slides Poster Similar
Complementing Representation Deficiency in Few-Shot Image Classification: A Meta-Learning Approach
Xian Zhong, Cheng Gu, Wenxin Huang, Lin Li, Shuqin Chen, Chia-Wen Lin
![Responsive image](/icpr/media/video_thumbnails/11172.jpg)
Auto-TLDR; Meta-learning with Complementary Representations Network for Few-Shot Learning
Abstract Slides Poster Similar
Price Suggestion for Online Second-Hand Items
Liang Han, Zhaozheng Yin, Zhurong Xia, Li Guo, Mingqian Tang, Rong Jin
![Responsive image](/icpr/media/video_thumbnails/11581.jpg)
Auto-TLDR; An Intelligent Price Suggestion System for Online Second-hand Items
Abstract Slides Poster Similar
Variational Capsule Encoder
Harish Raviprakash, Syed Anwar, Ulas Bagci
![Responsive image](/icpr/media/video_thumbnails/11569.jpg)
Auto-TLDR; Bayesian Capsule Networks for Representation Learning in latent space
Abstract Slides Poster Similar
Fast Discrete Cross-Modal Hashing Based on Label Relaxation and Matrix Factorization
Donglin Zhang, Xiaojun Wu, Zhen Liu, Jun Yu, Josef Kittler
![Responsive image](/icpr/media/video_thumbnails/11446.png)
Auto-TLDR; LRMF: Label Relaxation and Discrete Matrix Factorization for Cross-Modal Retrieval
Bayesian Active Learning for Maximal Information Gain on Model Parameters
Kasra Arnavaz, Aasa Feragen, Oswin Krause, Marco Loog
![Responsive image](/icpr/media/video_thumbnails/12160.jpg)
Auto-TLDR; Bayesian assumptions for Bayesian classification
Abstract Slides Poster Similar
Classification and Feature Selection Using a Primal-Dual Method and Projections on Structured Constraints
Michel Barlaud, Antonin Chambolle, Jean_Baptiste Caillau
![Responsive image](/icpr/media/thumbnails/1797_FI.pdf.jpg)
Auto-TLDR; A Constrained Primal-dual Method for Structured Feature Selection on High Dimensional Data
Abstract Slides Poster Similar
Naturally Constrained Online Expectation Maximization
Daniela Pamplona, Antoine Manzanera
![Responsive image](/icpr/media/video_thumbnails/11521.jpg)
Auto-TLDR; Constrained Online Expectation-Maximization for Probabilistic Principal Components Analysis
Abstract Slides Poster Similar
Low-Cost Lipschitz-Independent Adaptive Importance Sampling of Stochastic Gradients
Huikang Liu, Xiaolu Wang, Jiajin Li, Man-Cho Anthony So
![Responsive image](/icpr/media/video_thumbnails/11106.jpg)
Auto-TLDR; Adaptive Importance Sampling for Stochastic Gradient Descent
Multi-annotator Probabilistic Active Learning
Marek Herde, Daniel Kottke, Denis Huseljic, Bernhard Sick
![Responsive image](/icpr/media/video_thumbnails/12129.jpg)
Auto-TLDR; MaPAL: Multi-annotator Probabilistic Active Learning
Abstract Slides Poster Similar
Assortative-Constrained Stochastic Block Models
Daniel Gribel, Thibaut Vidal, Michel Gendreau
![Responsive image](/icpr/media/video_thumbnails/11619.jpg)
Auto-TLDR; Constrained Stochastic Block Models for Assortative Communities in Neural Networks
Abstract Slides Poster Similar
Adversarial Encoder-Multi-Task-Decoder for Multi-Stage Processes
Andre Mendes, Julian Togelius, Leandro Dos Santos Coelho
![Responsive image](/icpr/media/thumbnails/0389_FI.pdf.jpg)
Auto-TLDR; Multi-Task Learning and Semi-Supervised Learning for Multi-Stage Processes
Respecting Domain Relations: Hypothesis Invariance for Domain Generalization
Ziqi Wang, Marco Loog, Jan Van Gemert
![Responsive image](/icpr/media/video_thumbnails/12063.jpg)
Auto-TLDR; Learning Hypothesis Invariant Representations for Domain Generalization
Abstract Slides Poster Similar
Learning Natural Thresholds for Image Ranking
Somayeh Keshavarz, Quang Nhat Tran, Richard Souvenir
![Responsive image](/icpr/media/thumbnails/2300_FI.pdf.jpg)
Auto-TLDR; Image Representation Learning and Label Discretization for Natural Image Ranking
Abstract Slides Poster Similar
Constructing Geographic and Long-term Temporal Graph for Traffic Forecasting
Yiwen Sun, Yulu Wang, Kun Fu, Zheng Wang, Changshui Zhang, Jieping Ye
![Responsive image](/icpr/media/video_thumbnails/11272.jpg)
Auto-TLDR; GLT-GCRNN: Geographic and Long-term Temporal Graph Convolutional Recurrent Neural Network for Traffic Forecasting
Abstract Slides Poster Similar
On Resource-Efficient Bayesian Network Classifiers and Deep Neural Networks
Wolfgang Roth, Günther Schindler, Holger Fröning, Franz Pernkopf
![Responsive image](/icpr/media/video_thumbnails/12131.jpg)
Auto-TLDR; Quantization-Aware Bayesian Network Classifiers for Small-Scale Scenarios
Abstract Slides Poster Similar
Deep Convolutional Embedding for Digitized Painting Clustering
Giovanna Castellano, Gennaro Vessio
![Responsive image](/icpr/media/video_thumbnails/11176.jpg)
Auto-TLDR; A Deep Convolutional Embedding Model for Clustering Artworks
Abstract Slides Poster Similar
Meta Soft Label Generation for Noisy Labels
![Responsive image](/icpr/media/video_thumbnails/11736.jpg)
Auto-TLDR; MSLG: Meta-Learning for Noisy Label Generation
Abstract Slides Poster Similar
Exploiting Elasticity in Tensor Ranks for Compressing Neural Networks
Jie Ran, Rui Lin, Hayden Kwok-Hay So, Graziano Chesi, Ngai Wong
![Responsive image](/icpr/media/video_thumbnails/12077.jpg)
Auto-TLDR; Nuclear-Norm Rank Minimization Factorization for Deep Neural Networks
Abstract Slides Poster Similar
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm
Yun Yue, Ming Li, Venkatesh Saligrama, Ziming Zhang
![Responsive image](/icpr/media/video_thumbnails/12161.jpg)
Auto-TLDR; Frank-Wolfe Algorithm for Efficient Training of RNNs
Abstract Slides Poster Similar
VOWEL: A Local Online Learning Rule for Recurrent Networks of Probabilistic Spiking Winner-Take-All Circuits
Hyeryung Jang, Nicolas Skatchkovsky, Osvaldo Simeone
![Responsive image](/icpr/media/video_thumbnails/11414.jpg)
Auto-TLDR; VOWEL: A Variational Online Local Training Rule for Winner-Take-All Spiking Neural Networks