Ian Colbert

Orcid: 0000-0002-1669-5519

According to our database1, Ian Colbert authored at least 13 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
A2Q+: Improving Accumulator-Aware Weight Quantization.
CoRR, 2024

2023
Quantized Neural Networks for Low-Precision Accumulation with Guaranteed Overflow Avoidance.
CoRR, 2023

A2Q: Accumulator-Aware Quantization with Guaranteed Overflow Avoidance.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Robust Transferable Feature Extractors: Learning to Defend Pre-Trained Networks Against White Box Adversaries.
CoRR, 2022

Human-Like Navigation Behavior: A Statistical Evaluation Framework.
CoRR, 2022

Evaluating Navigation Behavior of Agents in Games using Non-Parametric Statistics.
Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

2021
Generating GPU Compiler Heuristics using Reinforcement Learning.
CoRR, 2021

Training Deep Neural Networks with Joint Quantization and Pruning of Weights and Activations.
CoRR, 2021

Generative and Discriminative Deep Belief Network Classifiers: Comparisons Under an Approximate Computing Framework.
CoRR, 2021

A Competitive Edge: Can FPGAs Beat GPUs at DCNN Inference Acceleration in Resource-Limited Edge Computing Applications?
CoRR, 2021

An Energy-Efficient Edge Computing Paradigm for Convolution-Based Image Upsampling.
IEEE Access, 2021

2019
AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks.
Proceedings of the International Joint Conference on Neural Networks, 2019

PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019


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