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Found 3 papers, 1 papers with code
Learning to Liquidate Forex: Optimal Stopping via Adaptive Top-K Regression
We consider learning a trading agent acting on behalf of the treasury of a firm earning revenue in a foreign currency (FC) and incurring expenses in the home currency (HC).
Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation
Most of the existing deep reinforcement learning (RL) approaches for session-based recommendations either rely on costly online interactions with real users, or rely on potentially biased rule-based or data-driven user-behavior models for learning.
NISER: Normalized Item and Session Representations to Handle Popularity Bias
The models using normalized item and session-graph representations perform significantly better: i. for the less popular long-tail items in the offline setting, and ii.
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Session-Based Recommendations
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