Ian Colbert

According to our database, Ian Colbert authored at least 26 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

MixQuant: Pushing the Limits of Block Rotations in Post-Training Quantization.

Sai Sanjeet, Ian Colbert, Pablo Monteagudo-Lago, Giuseppe Franco, Yaman Umuroglu, Nicholas J. Fraser

CoRR, January, 2026

GPU Acceleration of Sparse Fully Homomorphic Encrypted DNNs.

Lara D'Agata, Carlos Agulló-Domingo, Óscar Vera-López, Kaustubh Shivdikar, Ardhi W. B. Yudha, Ferhat Yaman, David R. Kaeli, José L. Abellán, Ian Colbert, José Cano

Proceedings of the Sixth European Workshop on Machine Learning and Systems, EuroMLSys 2026, 2026

2025

Combining Reinforcement Learning and Behavior Trees for NPCs in Video Games with AMD Schola.

Tian Liu, Alexander Cann, Ian Colbert, Mehdi Saeedi

CoRR, October, 2025

SIRA: Scaled-Integer Range Analysis for Optimizing FPGA Dataflow Neural Network Accelerators.

Yaman Umuroglu, Christoph Berganski, Felix Jentzsch, Michal Danilowicz, Tomasz Kryjak, Charalampos Bezaitis, Magnus Själander, Ian Colbert, Thomas B. Preußer, Jakoba Petri-Koenig, Michaela Blott

CoRR, August, 2025

Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos.

Haoyu Zhang, Shihao Zhang, Ian Colbert, Rayan Saab

CoRR, August, 2025

Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization.

Shihao Zhang, Haoyu Zhang, Ian Colbert, Rayan Saab

CoRR, May, 2025

Improving Quantization with Post-Training Model Expansion.

Giuseppe Franco, Pablo Monteagudo-Lago, Ian Colbert, Nicholas J. Fraser, Michaela Blott

CoRR, March, 2025

Accumulator-Aware Post-Training Quantization for Large Language Models.

Ian Colbert, Giuseppe Franco, Fabian Grob, Jinjie Zhang, Rayan Saab

Trans. Mach. Learn. Res., 2025

DPWatch: A Framework for Hardware-Based Differential Privacy Guarantees.

Pawan Kumar Sanjaya, Christina Giannoula, Ian Colbert, Ihab Amer, Mehdi Saeedi, Gabor Sines, Nandita Vijaykumar

IEEE Comput. Archit. Lett., 2025

Exploiting Unstructured Sparsity in Fully Homomorphic Encrypted DNNs.

Aidan Ferguson, Perry Gibson, Lara D'Agata, Parker McLeod, Ferhat Yaman, Amitabh Das, Ian Colbert, José Cano

Proceedings of the 5th Workshop on Machine Learning and Systems, 2025

Path Generation and Evaluation in Video Games: A Nonparametric Statistical Approach.

Daniel Campa, Mehdi Saeedi, Ian Colbert, Srinjoy Das

Proceedings of the IEEE Conference on Games, 2025

2024

Accumulator-Aware Post-Training Quantization.

Ian Colbert, Fabian Grob, Giuseppe Franco, Jinjie Zhang, Rayan Saab

CoRR, 2024

A2Q+: Improving Accumulator-Aware Weight Quantization.

Ian Colbert, Alessandro Pappalardo, Jakoba Petri-Koenig, Yaman Umuroglu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

End-to-End Inference Optimization for Deep Learning-based Image Upsampling Networks

Ian Colbert

PhD thesis, 2023

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

Ian Colbert, Alessandro Pappalardo, Jakoba Petri-Koenig

CoRR, 2023

A2Q: Accumulator-Aware Quantization with Guaranteed Overflow Avoidance.

Ian Colbert, Alessandro Pappalardo, Jakoba Petri-Koenig

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.

Alexander Cann, Ian Colbert, Ihab Amer

CoRR, 2022

Human-Like Navigation Behavior: A Statistical Evaluation Framework.

Ian Colbert, Mehdi Saeedi

CoRR, 2022

Evaluating Navigation Behavior of Agents in Games using Non-Parametric Statistics.

Ian Colbert, Mehdi Saeedi

Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

2021

Generating GPU Compiler Heuristics using Reinforcement Learning.

Ian Colbert, Jake Daly, Norm Rubin

CoRR, 2021

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

Xinyu Zhang, Ian Colbert, Kenneth Kreutz-Delgado, Srinjoy Das

CoRR, 2021

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

Siqiao Ruan, Ian Colbert, Kenneth Kreutz-Delgado, Srinjoy Das

CoRR, 2021

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

Ian Colbert, Jake Daly, Kenneth Kreutz-Delgado, Srinjoy Das

CoRR, 2021

An Energy-Efficient Edge Computing Paradigm for Convolution-Based Image Upsampling.

Ian Colbert, Kenneth Kreutz-Delgado, Srinjoy Das

IEEE Access, 2021

2019

AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks.

Ian Colbert, Kenneth Kreutz-Delgado, Srinjoy Das

Proceedings of the International Joint Conference on Neural Networks, 2019

PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems.

Alexander Potapov, Ian Colbert, Kenneth Kreutz-Delgado, Alexander Cloninger, Srinjoy Das

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019