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Found 7 papers, 2 papers with code
AI-coherent data-driven forecasting model for a combined cycle power plant
This study investigates the transformation of energy models to align with machine learning requirements as a promising tool for optimizing the operation of combined cycle power plants (CCPPs).
Practical Bandits: An Industry Perspective
The research literature on these topics is broad and vast, but this can overwhelm practitioners, whose primary aim is to solve practical problems, and therefore need to decide on a specific instantiation or approach for each project.
Episodes Discovery Recommendation with Multi-Source Augmentations
Recommender systems (RS) commonly retrieve potential candidate items for users from a massive number of items by modeling user interests based on historical interactions.
Sequential Recommendation via Stochastic Self-Attention
We further argue that BPR loss has no constraint on positive and sampled negative items, which misleads the optimization.
Current Challenges and Future Directions in Podcast Information Access
Podcasts are spoken documents across a wide-range of genres and styles, with growing listenership across the world, and a rapidly lowering barrier to entry for both listeners and creators.
Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste
Recommender systems are increasingly used to predict and serve content that aligns with user taste, yet the task of matching new users with relevant content remains a challenge.
The Engagement-Diversity Connection: Evidence from a Field Experiment on Spotify
We also observe evidence that our treatment affected streams from sections of Spotify's app not directly affected by the experiment, suggesting that exposure to personalized recommendations can affect the content that users consume organically.
