17 citations · 60 across the 34 of their papers we have counts for
8 papers · 1 filter
Augmenting Operations Research with Auto-Formulation of Optimization Models from Problem Descriptions
Rindranirina Ramamonjison, Haley Li, Timothy T. Yu +5
We describe an augmented intelligence system for simplifying and enhancing the modeling experience for operations research. Using this system, the user receives a suggested formula…
SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Grounding
Morgan Heisler, Amin Banitalebi-Dehkordi, Yong Zhang
Data augmentation is an essential technique in improving the generalization of deep neural networks. The majority of existing image-domain augmentations either rely on geometric an…
Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branch
Tianyu Zhang, Amin Banitalebi-Dehkordi, Yong Zhang
Branch-and-bound is a systematic enumerative method for combinatorial optimization, where the performance highly relies on the variable selection strategy. State-of-the-art handcra…
AuxMix: Semi-Supervised Learning with Unconstrained Unlabeled Data
Amin Banitalebi-Dehkordi, Pratik Gujjar, Yong Zhang
Semi-supervised learning (SSL) has seen great strides when labeled data is scarce but unlabeled data is abundant. Critically, most recent work assume that such unlabeled data is dr…
Spatial Cross-Attention Improves Self-Supervised Visual Representation Learning
Mehdi Seyfi, Amin Banitalebi-Dehkordi, Yong Zhang
Unsupervised representation learning methods like SwAV are proved to be effective in learning visual semantics of a target dataset. The main idea behind these methods is that diffe…
Extending Momentum Contrast with Cross Similarity Consistency Regularization
Mehdi Seyfi, Amin Banitalebi-Dehkordi, Yong Zhang
Contrastive self-supervised representation learning methods maximize the similarity between the positive pairs, and at the same time tend to minimize the similarity between the neg…
Asynchronous, Option-Based Multi-Agent Policy Gradient: A Conditional Reasoning Approach
Xubo Lyu, Amin Banitalebi-Dehkordi, Mo Chen +1
Cooperative multi-agent problems often require coordination between agents, which can be achieved through a centralized policy that considers the global state. Multi-agent policy g…
E-LANG: Energy-Based Joint Inferencing of Super and Swift Language Models
Mohammad Akbari, Amin Banitalebi-Dehkordi, Yong Zhang
Building huge and highly capable language models has been a trend in the past years. Despite their great performance, they incur high computational cost. A common solution is to ap…