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Home » Publication » Computer vision publications » Machine learning publications

Machine learning publications

Machine learning publications July 14, 2022

Incremental Learning with Differentiable Architecture and Forgetting Search

Han-Pang Chiu July 14, 2022

In this paper, we show that leveraging NAS for incremental learning results in strong performance gains for classification tasks.

Machine learning publications June 19, 2022

Saccade Mechanisms for Image Classification, Object Detection and Tracking

David Zhang June 19, 2022

Abstract We examine how the saccade mechanism from biological vision can be used to make deep neural networks more efficient for classification and object detection problems. Our proposed approach is based on the ideas of attention-driven visual processing and saccades, miniature eye movements influenced by attention. We conduct experiments by analyzing: i) the robustness of […]

Machine learning publications June 8, 2022

Conformal Prediction Intervals for Markov Decision Process Trajectories

SRI International June 8, 2022

This paper extends previous work on conformal prediction for functional data and conformalized quantile regression…

Machine learning publications April 8, 2022

Broadening AI Ethics Narratives: An Indic Arts View

Ajay Divakaran April 8, 2022

In this paper, we investigate uncovering the unique socio-cultural perspectives embedded in human-made art, which in turn, can be valuable in expanding the horizon of AI ethics.

Machine learning publications October 25, 2021

Generating and Evaluating Explanations of Attended and Error-Inducing Input Regions for VQA Models

Ajay Divakaran, Yi Yao October 25, 2021

Abstract Attention maps, a popular heatmap-based explanation method for Visual Question Answering (VQA), are supposed to help users understand the model by highlighting portions of the image/question used by the model to infer answers. However, we see that users are often misled by current attention map visualizations that point to relevant regions despite the model […]

Machine learning publications October 22, 2021

Challenges in Procedural Multimodal Machine Comprehension: A Novel Way to Benchmark

Ajay Divakaran October 22, 2021

We identify three critical biases stemming from the question-answer generation process and memorization capabilities of large deep models.

Machine learning publications July 14, 2021

“How to best say it?” : Translating Directives in Machine Language into Natural Language in the Blocks World

SRI International July 14, 2021

We propose a method to generate optimal natural language for block placement directives generated by a machine’s planner during human-agent interactions in the blocks world.

Machine learning publications June 8, 2021

Comprehension Based Question Answering Using Bloom’s Taxonomy

Ajay Divakaran, Sara Rutherford-Quach June 8, 2021

Abstract Current pre-trained language models have lots of knowledge, but a more limited ability to use that knowledge. Bloom’s Taxonomy helps educators teach children how to use knowledge by categorizing comprehension skills, so we use it to analyze and improve the comprehension skills of large pre-trained language models. Our experiments focus on zero-shot question answering, […]

Machine learning publications April 1, 2021

Modular Adaptation for Cross-Domain Few-Shot Learning

Ajay Divakaran, Yi Yao April 1, 2021

Abstract Adapting pre-trained representations has become the go-to recipe for learning new downstream tasks with limited examples. While literature has demonstrated great successes via representation learning, in this work, we show that substantial performance improvement of downstream tasks can also be achieved by appropriate designs of the adaptation process. Specifically, we propose a modular adaptation […]

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