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Found 7 papers, 3 papers with code
Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfaction
We present the Learned Ranking Function (LRF), a system that takes short-term user-item behavior predictions as input and outputs a slate of recommendations that directly optimizes for long-term user satisfaction.
Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach
A major challenge facing the world is the provision of equitable and universal access to quality education.
Analyzing and Improving Greedy 2-Coordinate Updates for Equality-Constrained Optimization via Steepest Descent in the 1-Norm
We show that bound- and summation-constrained steepest descent in the L1-norm guarantees more progress per iteration than previous rules and can be computed in only $O(n \log n)$ time.
Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning
Sparse and delayed rewards pose a challenge to single agent reinforcement learning.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
TF-GNN: Graph Neural Networks in TensorFlow
TensorFlow-GNN (TF-GNN) is a scalable library for Graph Neural Networks in TensorFlow.
ETA Prediction with Graph Neural Networks in Google Maps
Travel-time prediction constitutes a task of high importance in transportation networks, with web mapping services like Google Maps regularly serving vast quantities of travel time queries from users and enterprises alike.
Adversarial Computation of Optimal Transport Maps
We show that during training, our generator follows the $W_2$-geodesic between the initial and the target distributions.
