Dennis DeCoste

According to our database1, Dennis DeCoste authored at least 33 papers between 1990 and 2023.

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Bibliography

2023
SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network.
Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

2021
Training With Data Dependent Dynamic Learning Rates.
CoRR, 2021

2020
Stochastic Weight Averaging in Parallel: Large-Batch Training That Generalizes Well.
Proceedings of the 8th International Conference on Learning Representations, 2020

Memory Efficient 3D U-Net with Reversible Mobile Inverted Bottlenecks for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2019
Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2015
Hot Swapping for Online Adaptation of Optimization Hyperparameters.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Fast Approximate Matching of Videos from Hand-Held Cameras for Robust Background Subtraction.
Proceedings of the 2015 IEEE Winter Conference on Applications of Computer Vision, 2015

HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014
HD-CNN: Hierarchical Deep Convolutional Neural Network for Image Classification.
CoRR, 2014

Fast Approximate Matching of Cell-Phone Videos for Robust Background Subtraction.
CoRR, 2014

Compact Random Feature Maps.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Dense Non-rigid Point-Matching Using Random Projections.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2006
Building Support Vector Machines with Reduced Classifier Complexity.
J. Mach. Learn. Res., 2006

Automated Knowledge Discovery from Simulators.
Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

Naïve filterbots for robust cold-start recommendations.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

Collaborative prediction using ensembles of Maximum Margin Matrix Factorizations.
Proceedings of the Machine Learning, 2006

Ensembles of Nearest Neighbor Forecasts.
Proceedings of the Machine Learning: ECML 2006, 2006

2005
A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs.
J. Mach. Learn. Res., 2005

2004
An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels.
IEEE Trans. Neural Networks, 2004

2003
Anytime Query-Tuned Kernel Machines via Cholesky Factorization.
Proceedings of the Third SIAM International Conference on Data Mining, 2003

Sparse Greedy Minimax Probability Machine Classification.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Fast Query-Optimized Kernel Machine Classification Via Incremental Approximate Nearest Support Vectors.
Proceedings of the Machine Learning, 2003

2002
Training Invariant Support Vector Machines.
Mach. Learn., 2002

Anytime Interval-Valued Outputs for Kernel Machines: Fast Support Vector Machine Classification via Distance Geometry.
Proceedings of the Machine Learning, 2002

2000
Alpha seeding for support vector machines.
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000

1998
The Significance of Kasparov versus DEEP BLUE and the Future of Computer Chess.
J. Int. Comput. Games Assoc., 1998

1997
Making an Impact: Artificial Intelligence at the Jet Propulsion Laboratory.
AI Mag., 1997

Mining Multivariate Time-Series Sensor Data to Discover Behavior Envelopes.
Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), 1997

The Future of Chess-Playing Technologies and the Significance of Kasparov Versus deep Blue.
Proceedings of the Deep Blue Versus Kasparov: The Significance for Artificial Intelligence, 1997

1991
Dynamic Across-Time Measurement Interpretation.
Artif. Intell., 1991

CATMS: An ATMS Which Avoids Label Explosions.
Proceedings of the 9th National Conference on Artificial Intelligence, 1991

1990
Dynamic Acioss-Time Measurement Interpretation.
Proceedings of the 8th National Conference on Artificial Intelligence. Boston, Massachusetts, USA, July 29, 1990


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