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02/09/2023
IH-ViT: Vision Transformer-based Integrated Circuit Appear-ance Defect Detection
For the problems of low recognition rate and slow recognition speed of t...
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10/13/2022
Adaptive A/B Tests and Simultaneous Treatment Parameter Optimization
Constructing asymptotically valid confidence intervals through a valid c...
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06/21/2021
ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction
Natural reading orders of words are crucial for information extraction f...
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03/19/2020
Affinity Graph Supervision for Visual Recognition
Affinity graphs are widely used in deep architectures, including graph c...
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06/04/2019
Dominant Set Clustering and Pooling for Multi-View 3D Object Recognition
View based strategies for 3D object recognition have proven to be very s...
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05/27/2019
FAN: Focused Attention Networks
Attention networks show promise for both vision and language tasks, by e...
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04/18/2019
ProductNet: a Collection of High-Quality Datasets for Product Representation Learning
ProductNet is a collection of high-quality product datasets for better p...
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04/11/2019
Reference Product Search
For a product of interest, we propose a search method to surface a set o...
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08/01/2018
Anomaly Detection via Minimum Likelihood Generative Adversarial Networks
Anomaly detection aims to detect abnormal events by a model of normality...
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03/15/2018
Local Spectral Graph Convolution for Point Set Feature Learning
Feature learning on point clouds has shown great promise, with the intro...
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09/13/2017
Optimal Learning for Sequential Decision Making for Expensive Cost Functions with Stochastic Binary Feedbacks
We consider the problem of sequentially making decisions that are reward...
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07/21/2017
A New Family of Near-metrics for Universal Similarity
We propose a family of near-metrics based on local graph diffusion to ca...
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09/13/2016
Self-Sustaining Iterated Learning
An important result from psycholinguistics (Griffiths & Kalish, 2005) st...
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10/09/2015
Functional Frank-Wolfe Boosting for General Loss Functions
Boosting is a generic learning method for classification and regression....
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10/08/2015
