Search Results for author:
Found 14 papers, 7 papers with code
Investigating Capsule Networks with Dynamic Routing for Text Classification
In this study, we explore capsule networks with dynamic routing for text classification.
Ranked #7 on
Sentiment Analysis
on MR
Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers
Model pruning has become a useful technique that improves the computational efficiency of deep learning, making it possible to deploy solutions in resource-limited scenarios.
A Faster Drop-in Implementation for Leaf-wise Exact Greedy Induction of Decision Tree Using Pre-sorted Deque
This short article presents a new implementation for decision trees.
Data Structures and Algorithms
Fast Discrete Distribution Clustering Using Wasserstein Barycenter with Sparse Support
In a variety of research areas, the weighted bag of vectors and the histogram are widely used descriptors for complex objects.
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the Wild
A system to model the emotional expressions based on bodily movements, named ARBEE (Automated Recognition of Bodily Expression of Emotion), has also been developed and evaluated.
Probabilistic Multigraph Modeling for Improving the Quality of Crowdsourced Affective Data
We proposed a probabilistic approach to joint modeling of participants' reliability and humans' regularity in crowdsourced affective studies.
A Distance for HMMs based on Aggregated Wasserstein Metric and State Registration
We refer to such HMMs as Gaussian mixture model-HMM (GMM-HMM).
Detecting Comma-shaped Clouds for Severe Weather Forecasting using Shape and Motion
Meteorologists use shapes and movements of clouds in satellite images as indicators of several major types of severe storms.
Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations
Strict partial order is a mathematical structure commonly seen in relational data.
Aggregated Wasserstein Metric and State Registration for Hidden Markov Models
This distance quantifies the dissimilarity of GMM-HMMs by measuring both the difference between the two marginal GMMs and that between the two transition matrices.
Multiple Closed-Form Local Metric Learning for K-Nearest Neighbor Classifier
Many researches have been devoted to learn a Mahalanobis distance metric, which can effectively improve the performance of kNN classification.
Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering
The new clustering method is easy to use and consistently outperforms other methods on a variety of data sets.
Leveraging Long and Short-Term Information in Content-Aware Movie Recommendation via Adversarial Training
Movie recommendation systems provide users with ranked lists of movies based on individual’s preferences and constraints.
Fast Sparse View Guided NeRF Update for Object Reconfigurations
Neural Radiance Field (NeRF), as an implicit 3D scene representation, lacks inherent ability to accommodate changes made to the initial static scene.
