Porter Jenkins

22 papers A* 9A 3Journal 6Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Provable and Practical In-Context Policy Optimization for Self-Improvement.
CoRR
Tianrun Yu, Yuxiao Yang, Zhaoyang Wang, Kaixiang Zhao, Porter Jenkins, Xuchao Zhang, Chetan Bansal, Huaxiu Yao, Weitong Zhang
2025 A conf
Assessing the Probabilistic Fit of Neural Regressors via Conditional Congruence.
ECAI
Spencer Young, Riley Sinema, Cole Edgren, Andrew Hall, Nathan Dong, Porter Jenkins
2025 A* conf
Fully Heteroscedastic Count Regression with Deep Double Poisson Networks.
ICML
Spencer Young, Porter Jenkins, Longchao Da, Jeffrey Dotson, Hua Wei
2024 J jnl
Flexible Heteroscedastic Count Regression with Deep Double Poisson Networks.
CoRR
Spencer Young, Porter Jenkins, Longchao Da, Jeffrey Dotson, Hua Wei
2024 — conf
Head Tail Open: Open Tailed Classification of Imbalanced Document Data.
SAI (1)
Chetan Joshi, Daniel Segrera, Lawry Sorenson, Mark J. Clement, Bryan S. Morse, Porter Jenkins, Taylor Archibald, M. J. Ghorbani
2024 J jnl
On Measuring Calibration of Discrete Probabilistic Neural Networks.
CoRR
Spencer Young, Porter Jenkins
2024 A* conf
Personalized Product Assortment with Real-time 3D Perception and Bayesian Payoff Estimation.
KDD
Porter Jenkins, Michael Selander, J. Stockton Jenkins, Andrew Merrill, Kyle Armstrong
2024 J jnl
Personalized Product Assortment with Real-time 3D Perception and Bayesian Payoff Estimation.
CoRR
Porter Jenkins, Michael Selander, J. Stockton Jenkins, Andrew Merrill, Kyle Armstrong
2024 A* conf
Probabilistic Offline Policy Ranking with Approximate Bayesian Computation.
AAAI
Longchao Da, Porter Jenkins, Trevor Schwantes, Jeffrey Dotson, Hua Wei
2023 A conf
CountNet3D: A 3D Computer Vision Approach to Infer Counts of Occluded Objects.
WACV
Porter Jenkins, Kyle Armstrong, Stephen Nelson, Siddhesh Gotad, J. Stockton Jenkins, Wade Wilkey, Tanner Watts
2023 J jnl
Probabilistic Offline Policy Ranking with Approximate Bayesian Computation.
CoRR
Longchao Da, Porter Jenkins, Trevor Schwantes, Jeffrey Dotson, Hua Wei
2022 A* conf
Bayesian Model-Based Offline Reinforcement Learning for Product Allocation.
AAAI
Porter Jenkins, Hua Wei, J. Stockton Jenkins, Zhenhui Li
2021 A* conf
Knowledge-based Residual Learning.
IJCAI
Guanjie Zheng, Chang Liu, Hua Wei, Porter Jenkins, Chacha Chen, Tao Wen, Zhenhui Li
2021 A* conf
Neural Utility Functions.
AAAI
Porter Jenkins, Ahmad Farag, J. Stockton Jenkins, Huaxiu Yao, Suhang Wang, Zhenhui Li
2021 A* conf
Overview of the 1st Workshop on City Brain Research.
KDD
Guanjie Zheng, Porter Jenkins, Yanyan Xu, Dongyao Chen
2021 — conf
Probabilistic simulation of spatial demand for intelligent product allocation.
GeoSim@SIGSPATIAL
Porter Jenkins, Hua Wei, J. Stockton Jenkins, Zhenhui Li
2020 J jnl
A Probabilistic Simulator of Spatial Demand for Product Allocation.
CoRR
Porter Jenkins, Hua Wei, J. Stockton Jenkins, Zhenhui Li
2020 A* conf
Natural Language Annotations for Search Engine Optimization.
WWW
Porter Jenkins, Jennifer Zhao, Heath Vinicombe, Anant Subramanian, Arun Prasad, Atillia Dobi, Eileen Li, Yunsong Guo
2020 — conf
Structured Paragraph Embeddings of Financial Earnings Calls.
WWW (Companion Volume)
Porter Jenkins
2019 — conf
ClickGraph: Web Page Embedding using Clickstream Data for Multitask Learning.
WWW (Companion Volume)
Porter Jenkins
2019 A* conf
Learning Task-Specific City Region Partition.
WWW
Hongjian Wang, Porter Jenkins, Hua Wei, Fei Wu, Zhenhui Li
2019 A conf
Unsupervised Representation Learning of Spatial Data via Multimodal Embedding.
CIKM
Porter Jenkins, Ahmad Farag, Suhang Wang, Zhenhui Li