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Learning to Stop Cut Generation for Efficient Mixed-Integer Linear Programming

A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability (Spotlight)

Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction

State Sequences Prediction via Fourier Transform for Representation Learning (Spotlight)

De Novo Molecular Generation via Connection-aware Motif Mining

Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model

LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence (Spotlight)

Efficient Exploration in Resource-Restricted Reinforcement Learning

Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent Variables

Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation