Search Results for author:
Found 12 papers, 4 papers with code
Collaborative Residual Metric Learning
In collaborative filtering, distance metric learning has been applied to matrix factorization techniques with promising results.
Modeling sequential annotations for sequence labeling with crowds
To accelerate the marginalization of the proposed model, a valid label sequence inference (VLSE) method is proposed to derive the valid ground-truth label sequences from crowd sequential annotations.
Weak Disambiguation for Partial Structured Output Learning
Existing disambiguation strategies for partial structured output learning just cannot generalize well to solve the problem that there are some candidates which can be false positive or similar to the ground-truth label.
Partial sequence labeling with structured Gaussian Processes
Then confidence measure is introduced in the model to address different contributions of candidate labels, which enables the ground-truth label information to be utilized in parameter learning.
Duration modeling with semi-Markov Conditional Random Fields for keyphrase extraction
Existing methods for keyphrase extraction need preprocessing to generate candidate phrase or post-processing to transform keyword into keyphrase.
Fine-tuning Partition-aware Item Similarities for Efficient and Scalable Recommendation
In this paper, we investigate the graph sampling strategy adopted in latest GCN model for efficiency improving, and identify the potential item group structure in the sampled graph.
Learning with fuzzy hypergraphs: a topical approach to query-oriented text summarization
As each topic defines a semantic connection among a group of sentences with a certain degree of membership for each sentence, we propose a fuzzy hypergraph model in which nodes are sentences and fuzzy hyperedges are topics.
Query-oriented text summarization based on hypergraph transversals
Existing graph- and hypergraph-based algorithms for document summarization represent the sentences of a corpus as the nodes of a graph or a hypergraph in which the edges represent relationships of lexical similarities between sentences.
Exactly Robust Kernel Principal Component Analysis
RKPCA can be applied to many problems such as noise removal and subspace clustering and is still the only unsupervised nonlinear method robust to sparse noises.
Mutual Information-Based Unsupervised Feature Transformation for Heterogeneous Feature Subset Selection
Conventional mutual information (MI) based feature selection (FS) methods are unable to handle heterogeneous feature subset selection properly because of data format differences or estimation methods of MI between feature subset and class label.
Probabilistic fault detector for Wireless Sensor Network
To maximize the network s life, the proposed method, Centralized Naïve Bayes Detector (CNBD) analyzes the end-to-end transmission time collected at the sink.
Passive Diagnosis for Wireless Sensor Networks
To maximize the network s life, the proposed method, Centralized Naïve Bayes Detector (CNBD) analyzes the end-to-end transmission time collected at the sink.
