Subutai Ahmad - researchr alias

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 29 from 29

2023

Supercharged AI Inference on Modern CPUsLawrence Spracklen, Subutai Ahmad. hotchips 2023: 1-21 [doi]

2022

Two sparsities are better than one: unlocking the performance benefits of sparse-sparse networksKevin Lee Hunter, Lawrence Spracklen, Subutai Ahmad. neuromorphic, 2(3):34004, 2022. [doi]

Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic EnvironmentsAbhiram Iyer, Karan Grewal, Akash Velu, Lucas Oliveira Souza, Jeremy Forest, Subutai Ahmad. finr, 16:846219, 2022. [doi]

2021

2020

Long Distance Relationships Without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence ModelingJeremy Gordon, David Rawlinson, Subutai Ahmad. annpr 2020: 52-64 [doi]

2019

Biologically Driven Artificial IntelligenceKjell J. Hole, Subutai Ahmad. Computer, 52(8):72-75, 2019. [doi]

2018

A Sequence-Based Neuronal Model for Mobile Robot LocalizationPeer Neubert, Subutai Ahmad, Peter Protzel. ki 2018: 117-130 [doi]

2017

Unsupervised real-time anomaly detection for streaming dataSubutai Ahmad, Alexander Lavin, Scott Purdy, Zuha Agha. ijon, 262:134-147, 2017. [doi]

The HTM Spatial Pooler - A Neocortical Algorithm for Online Sparse Distributed CodingYuwei Cui, Subutai Ahmad, Jeff Hawkins. ficn, 2017:111, 2017. [doi]

2016

A comparative study of HTM and other neural network models for online sequence learning with streaming dataYuwei Cui, Chetan Surpur, Subutai Ahmad, Jeff Hawkins. ijcnn 2016: 1530-1538 [doi]

Continuous Online Sequence Learning with an Unsupervised Neural Network ModelYuwei Cui, Subutai Ahmad, Jeff Hawkins. neco, 28(11):2474-2504, 2016. [doi]

2015

Evaluating Real-Time Anomaly Detection Algorithms - The Numenta Anomaly BenchmarkAlexander Lavin, Subutai Ahmad. icmla 2015: 38-44 [doi]

2012

Automated machine learning for autonomic computingSubutai Ahmad. icac 2012: 103-104 [doi]

2002

Analysis-by-synthesis dissolve detectionMichele Covell, Subutai Ahmad. icip 2002: 425-428

1997

Representing Probabilistic Rules with Networks of Gaussian Basis FunctionsVolker Tresp, Jürgen Hollatz, Subutai Ahmad. ml, 27(2):173-200, 1997.

1994

Efficient Methods for Dealing with Missing Data in Supervised LearningVolker Tresp, Ralph Neuneier, Subutai Ahmad. nips 1995: 689-696 [doi]

1993

Feature Densities Are Required for Computing Feature CorrespondencesSubutai Ahmad. nips 1994: 961-968 [doi]

David Touretzky, Jeffrey Elman, Terrence Sejnowski and Geoffrey Hinton, eds., Connectionist Models: Proceedings of the 1990 Summer SchoolSubutai Ahmad. ai, 62(1):117-127, 1993.

Classification with missing and uncertain inputsSubutai Ahmad, Volker Tresp. icnn 1993: 1949-1954 [doi]

Training Neural Networks with Deficient DataVolker Tresp, Subutai Ahmad, Ralph Neuneier. nips 1994: 128-135 [doi]

1992

Some Solutions to the Missing Feature Problem in VisionSubutai Ahmad, Volker Tresp. nips 1993: 393-400 [doi]

Network Structuring and Training Using Rule-Based KnowledgeVolker Tresp, Jürgen Hollatz, Subutai Ahmad. nips 1993: 871-878 [doi]

1991

VISIT: A Neural Model of Covert Visual AttentionSubutai Ahmad. nips 1992: 420-427 [doi]

VISIT: An efficient computational model of human visual attentionSubutai Ahmad. PhD thesis, University of Illinois Urbana-Champaign, USA, 1991. [doi]

1989

Asymptotic Convergence of Backpropagation: Numerical ExperimentsSubutai Ahmad, Gerald Tesauro, Yu He. nips 1990: 606-613 [doi]

Asymptotic Convergence of BackpropagationGerald Tesauro, Yu He, Subutai Ahmad. neco, 1(3):382-391, 1989. [doi]

1988

Scaling and Generalization in Neural Networks: A Case StudySubutai Ahmad, Gerald Tesauro. nips 1989: 160-168 [doi]

A study of scaling and generalization in neural networksSubutai Ahmad, Gerald Tesauro. NN, 1(Supplement-1):3-6, 1988. [doi]

Sign in or sign up to see more results.

runs on WebDSL