Search Results for author: David Chan

Found 9 papers, 1 papers with code

LAVA: Language Audio Vision Alignment for Contrastive Video Pre-Training

no code implementations16 Jul 2022 Sumanth Gurram, Andy Fang, David Chan, John Canny

Generating representations of video data is of key importance in advancing the field of machine perception.

Action Recognition Contrastive Learning

Misinformation Detection in Social Media Video Posts

no code implementations15 Feb 2022 Kehan Wang, David Chan, Seth Z. Zhao, John Canny, Avideh Zakhor

With the growing adoption of short-form video by social media platforms, reducing the spread of misinformation through video posts has become a critical challenge for social media providers.

Contrastive Learning Language Modelling +3

Decision Tree-Based Predictive Models for Academic Achievement Using College Students' Support Networks

no code implementations31 Aug 2021 Anthony Frazier, Joethi Silva, Rachel Meilak, Indranil Sahoo, David Chan, Michael Broda

For White students, different types of educational support were important in predicting academic achievement, while for non-White students, different types of emotional support were important in predicting academic achievement.

A Dataset and Benchmarks for Multimedia Social Analysis

no code implementations5 Jun 2020 Bofan Xue, David Chan, John Canny

We present a new publicly available dataset with the goal of advancing multi-modality learning by offering vision and language data within the same context.

Image Captioning Image Classification +2

ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations

2 code implementations26 Oct 2019 Daniel Seita, David Chan, Roshan Rao, Chen Tang, Mandi Zhao, John Canny

Learning from demonstrations is a popular tool for accelerating and reducing the exploration requirements of reinforcement learning.

Atari Games Q-Learning +1

Leveraging Class Similarity to Improve Deep Neural Network Robustness

no code implementations23 Dec 2018 Pooran Singh Negi, David Chan, Mohammad Mahoor

Traditionally artificial neural networks (ANNs) are trained by minimizing the cross-entropy between a provided groundtruth delta distribution (encoded as one-hot vector) and the ANN's predictive softmax distribution.

Bias Correction For Paid Search In Media Mix Modeling

no code implementations9 Jul 2018 Aiyou Chen, David Chan, Mike Perry, Yuxue Jin, Yunting Sun, Yueqing Wang, Jim Koehler

Evaluating the return on ad spend (ROAS), the causal effect of advertising on sales, is critical to advertisers for understanding the performance of their existing marketing strategy as well as how to improve and optimize it.


Going Deeper in Facial Expression Recognition using Deep Neural Networks

no code implementations12 Nov 2015 Ali Mollahosseini, David Chan, Mohammad H. Mahoor

Despite efforts made in developing various methods for FER, existing approaches traditionally lack generalizability when applied to unseen images or those that are captured in wild setting.

Facial Expression Recognition

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