29 citations · 70 across the 19 of their papers we have counts for
6 papers · 1 filter
Deep Policy Iteration with Integer Programming for Inventory Management
Pavithra Harsha, Ashish Jagmohan, Jayant Kalagnanam +2
We present a Reinforcement Learning (RL) based framework for optimizing long-term discounted reward problems with large combinatorial action space and state dependent constraints.…
Learning to shortcut and shortlist order fulfillment deciding
Brian Quanz, Ajay Deshpande, Dahai Xing +1
With the increase of order fulfillment options and business objectives taken into consideration in the deciding process, order fulfillment deciding is becoming more and more comple…
Predicting Deep Neural Network Generalization with Perturbation Response Curves
Yair Schiff, Brian Quanz, Payel Das +1
The field of Deep Learning is rich with empirical evidence of human-like performance on a variety of prediction tasks. However, despite these successes, the recent Predicting Gener…
Towards creativity characterization of generative models via group-based subset scanning
Celia Cintas, Payel Das, Brian Quanz +3
Deep generative models, such as Variational Autoencoders (VAEs), have been employed widely in computational creativity research. However, such models discourage out-of-distribution…
Gi and Pal Scores: Deep Neural Network Generalization Statistics
Yair Schiff, Brian Quanz, Payel Das +1
The field of Deep Learning is rich with empirical evidence of human-like performance on a variety of regression, classification, and control tasks. However, despite these successes…
Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting
Nam Nguyen, Brian Quanz
Probabilistic forecasting of high dimensional multivariate time series is a notoriously challenging task, both in terms of computational burden and distribution modeling. Most prev…