Search Results for author:
Found 8 papers, 3 papers with code
Ranking with Slot Constraints
We introduce the problem of ranking with slot constraints, which can be used to model a wide range of application problems -- from college admission with limited slots for different majors, to composing a stratified cohort of eligible participants in a medical trial.
Node-Aligned Graph-to-Graph Generation for Retrosynthesis Prediction
Furthermore, our approach simplifies the incorporation of production-reactant atom mapping alignment by leveraging node alignment to determine a specific order for node generation and generating molecular graphs in an auto-regressive manner node-by-node.
Assessing the efficacy of large language models in generating accurate teacher responses
(Tack et al., 2023) organized the shared task hosted by the 18th Workshop on Innovative Use of NLP for Building Educational Applications on generation of teacher language in educational dialogues.
Photo Rater: Photographs Auto-Selector with Deep Learning
Photo Rater is a computer vision project that uses neural networks to help photographers select the best photo among those that are taken based on the same scene.
MCTensor: A High-Precision Deep Learning Library with Multi-Component Floating-Point
In this paper, we introduce MCTensor, a library based on PyTorch for providing general-purpose and high-precision arithmetic for DL training.
Cyclical Kernel Adaptive Metropolis
We propose cKAM, cyclical Kernel Adaptive Metropolis, which incorporates a cyclical stepsize scheme to allow control for exploration and sampling.
GraB: Finding Provably Better Data Permutations than Random Reshuffling
To reduce the memory overhead, we leverage discrepancy minimization theory to propose an online Gradient Balancing algorithm (GraB) that enjoys the same rate as herding, while reducing the memory usage from $O(nd)$ to just $O(d)$ and computation from $O(n^2)$ to $O(n)$, where $d$ denotes the model dimension.
Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm
With the transition from people's traditional `brick-and-mortar' shopping to online mobile shopping patterns in web 2. 0 $\mathit{era}$, the recommender system plays a critical role in E-Commerce and E-Retails.
