Dynamic Acioss-Time Measurement Interpretation. - Dennis DeCoste (AAAI, 1990)

CATMS: An ATMS Which Avoids Label Explosions. - John W. Collins; Dennis DeCoste (AAAI, 1991)

Dynamic Across-Time Measurement Interpretation. - Dennis DeCoste (Artif. Intell., 1991)

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

Mining Multivariate Time-Series Sensor Data to Discover Behavior Envelopes. - Dennis DeCoste (KDD, 1997)

Making an Impact: Artificial Intelligence at the Jet Propulsion Laboratory. - Steve A. Chien; Dennis DeCoste; Richard J. Doyle; Paul E. Stolorz (AI Mag., 1997)

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

Alpha seeding for support vector machines. - Dennis DeCoste; Kiri Wagstaff (KDD, 2000)

Anytime Interval-Valued Outputs for Kernel Machines: Fast Support Vector Machine Classification via Distance Geometry. - Dennis DeCoste (ICML, 2002)

Training Invariant Support Vector Machines. - Dennis DeCoste; Bernhard Schölkopf (Mach. Learn., 2002)

Fast Query-Optimized Kernel Machine Classification Via Incremental Approximate Nearest Support Vectors. - Dennis DeCoste; Dominic Mazzoni (ICML, 2003)

Sparse Greedy Minimax Probability Machine Classification. - Thomas Strohmann; Andrei Belitski; Gregory Z. Grudic; Dennis DeCoste (NIPS, 2003)

Anytime Query-Tuned Kernel Machines via Cholesky Factorization. - Dennis DeCoste (SDM, 2003)

An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels. - Martin M. S. Lee; S. Sathiya Keerthi; Chong Jin Ong; Dennis DeCoste (IEEE Trans. Neural Networks, 2004)

A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs. - S. Sathiya Keerthi; Dennis DeCoste (J. Mach. Learn. Res., 2005)

Ensembles of Nearest Neighbor Forecasts. - Dragomir Yankov; Dennis DeCoste; Eamonn J. Keogh (ECML, 2006)

Collaborative prediction using ensembles of Maximum Margin Matrix Factorizations. - Dennis DeCoste (ICML, 2006)

Naïve filterbots for robust cold-start recommendations. - Seung-Taek Park; David M. Pennock; Omid Madani; Nathan Good; Dennis DeCoste (KDD, 2006)

Automated Knowledge Discovery from Simulators. - Michael C. Burl; Dennis DeCoste; Brian L. Enke; Dominic Mazzoni; William J. Merline; Lucas Scharenbroich (SDM, 2006)

Building Support Vector Machines with Reduced Classifier Complexity. - S. Sathiya Keerthi; Olivier Chapelle; Dennis DeCoste (J. Mach. Learn. Res., 2006)

Dense Non-rigid Point-Matching Using Random Projections. - Raffay Hamid; Dennis DeCoste; Chih-Jen Lin (CVPR, 2013)

Compact Random Feature Maps. - Raffay Hamid; Ying Xiao 003; Alex Gittens; Dennis DeCoste (ICML, 2014)

Fast Approximate Matching of Cell-Phone Videos for Robust Background Subtraction. - Raffay Hamid; Atish Das Sarma; Dennis DeCoste; Neel Sundaresan (CoRR, 2014)

HD-CNN: Hierarchical Deep Convolutional Neural Network for Image Classification. - Zhicheng Yan 001; Vignesh Jagadeesh; Dennis DeCoste; Wei Di; Robinson Piramuthu (CoRR, 2014)

HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition. - Zhicheng Yan 001; Hao Zhang 025; Robinson Piramuthu; Vignesh Jagadeesh; Dennis DeCoste; Wei Di; Yizhou Yu (ICCV, 2015)

Fast Approximate Matching of Videos from Hand-Held Cameras for Robust Background Subtraction. - Raffay Hamid; Atish Das Sarma; Dennis DeCoste; Neel Sundaresan (WACV, 2015)

Hot Swapping for Online Adaptation of Optimization Hyperparameters. - Kevin Bache; Dennis DeCoste; Padhraic Smyth (ICLR (Workshop), 2015)

Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum. - Shreyas Saxena; Oncel Tuzel; Dennis DeCoste (NeurIPS, 2019)

Memory Efficient 3D U-Net with Reversible Mobile Inverted Bottlenecks for Brain Tumor Segmentation. - Mihir Pendse; Vithursan Thangarasa; Vitaliy Chiley; Ryan Holmdahl; Joel Hestness; Dennis DeCoste (BrainLes@MICCAI (2), 2020)

Stochastic Weight Averaging in Parallel: Large-Batch Training That Generalizes Well. - Vipul Gupta; Santiago Akle Serrano; Dennis DeCoste (ICLR, 2020)

Training With Data Dependent Dynamic Learning Rates. - Shreyas Saxena; Nidhi Vyas; Dennis DeCoste (CoRR, 2021)

RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network. - Vitaliy Chiley; Vithursan Thangarasa; Abhay Gupta; Anshul Samar; Joel Hestness; Dennis DeCoste (MLSys, 2023)

SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models. - Vithursan Thangarasa; Abhay Gupta; William Marshall; Tianda Li; Kevin Leong; Dennis DeCoste; Sean Lie; Shreyas Saxena (UAI, 2023)