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11/28/2022
Long-tail Cross Modal Hashing
Existing Cross Modal Hashing (CMH) methods are mainly designed for balan...
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11/28/2022
Incentive-boosted Federated Crowdsourcing
Crowdsourcing is a favorable computing paradigm for processing computer-...
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11/18/2022
Hub-VAE: Unsupervised Hub-based Regularization of Variational Autoencoders
Exemplar-based methods rely on informative data points or prototypes to ...
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11/07/2021
MetaMIML: Meta Multi-Instance Multi-Label Learning
Multi-Instance Multi-Label learning (MIML) models complex objects (bags)...
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11/07/2021
Meta Cross-Modal Hashing on Long-Tailed Data
Due to the advantage of reducing storage while speeding up query time on...
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11/07/2021
Cross-modal Zero-shot Hashing by Label Attributes Embedding
Cross-modal hashing (CMH) is one of the most promising methods in cross-...
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11/07/2021
Open-Set Crowdsourcing using Multiple-Source Transfer Learning
We raise and define a new crowdsourcing scenario, open set crowdsourcing...
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11/07/2021
Crowdsourcing with Meta-Workers: A New Way to Save the Budget
Due to the unreliability of Internet workers, it's difficult to complete...
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07/09/2021
Group-Node Attention for Community Evolution Prediction
Communities in social networks evolve over time as people enter and leav...
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06/02/2021
Few-Shot Partial-Label Learning
Partial-label learning (PLL) generally focuses on inducing a noise-toler...
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10/20/2020
Unsupervised Selective Manifold Regularized Matrix Factorization
Manifold regularization methods for matrix factorization rely on the clu...
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10/07/2020
Effects of Model Misspecification on Bayesian Bandits: Case Studies in UX Optimization
Bayesian bandits using Thompson Sampling have seen increasing success in...
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10/06/2020
Multi-typed Objects Multi-view Multi-instance Multi-label Learning
Multi-typed objects Multi-view Multi-instance Multi-label Learning (M4L)...
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10/02/2020
Deep Incomplete Multi-View Multiple Clusterings
Multi-view clustering aims at exploiting information from multiple heter...
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12/24/2019
Attention-Aware Answers of the Crowd
Crowdsourcing is a relatively economic and efficient solution to collect...
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11/07/2019
Active Multi-Label Crowd Consensus
Crowdsourcing is an economic and efficient strategy aimed at collecting ...
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10/22/2019
Unsupervised Boosting-based Autoencoder Ensembles for Outlier Detection
Autoencoders, as a dimensionality reduction technique, have been recentl...
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10/18/2019
Estimator Vectors: OOV Word Embeddings based on Subword and Context Clue Estimates
Semantic representations of words have been successfully extracted from ...
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08/19/2019
Cross-modal Zero-shot Hashing
Hashing has been widely studied for big data retrieval due to its low st...
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05/29/2019
Weakly-paired Cross-Modal Hashing
Hashing has been widely adopted for large-scale data retrieval in many d...
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05/14/2019
ActiveHNE: Active Heterogeneous Network Embedding
Heterogeneous network embedding (HNE) is a challenging task due to the d...
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05/13/2019
Multi-View Multi-Instance Multi-Label Learning based on Collaborative Matrix Factorization
Multi-view Multi-instance Multi-label Learning(M3L) deals with complex o...
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05/13/2019
Multi-View Multiple Clustering
Multiple clustering aims at exploring alternative clusterings to organiz...
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05/11/2019
Ranking-based Deep Cross-modal Hashing
Cross-modal hashing has been receiving increasing interests for its low ...
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05/10/2019
Multiple Independent Subspace Clusterings
Multiple clustering aims at discovering diverse ways of organizing data ...
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04/17/2018