4 citations · 9 across the 8 of their papers we have counts for
8 papers
AlignUSER: Human-Aligned LLM Agents via World Models for Recommender System Evaluation
Nicolas Bougie, Gian Maria Marconi, Tony Yip +1
Evaluating recommender systems remains challenging due to the gap between offline metrics and real user behavior, as well as the scarcity of interaction data. Recent work explores…
Variational Learning Induces Adaptive Label Smoothing
Sin-Han Yang, Zhedong Liu, Gian Maria Marconi +1
We show that variational learning naturally induces an adaptive label smoothing where label noise is specialized for each example. Such label-smoothing is useful to handle examples…
Variational Learning is Effective for Large Deep Networks
Yuesong Shen, Nico Daheim, Bai Cong +8
We give extensive empirical evidence against the common belief that variational learning is ineffective for large neural networks. We show that an optimizer called Improved Variati…
Bridging the Gap Between Target Networks and Functional Regularization
Alexandre Piche, Valentin Thomas, Joseph Marino +4
Bootstrapping is behind much of the successes of Deep Reinforcement Learning. However, learning the value function via bootstrapping often leads to unstable training due to fast-ch…
Bridging the Gap Between Target Networks and Functional Regularization
Alexandre Piché, Valentin Thomas, Rafael Pardinas +4
Bootstrapping is behind much of the successes of deep Reinforcement Learning. However, learning the value function via bootstrapping often leads to unstable training due to fast-ch…
Structured Prediction for CRiSP Inverse Kinematics Learning with Misspecified Robot Models
Gian Maria Marconi, Raffaello Camoriano, Lorenzo Rosasco +1
With the recent advances in machine learning, problems that traditionally would require accurate modeling to be solved analytically can now be successfully approached with data-dri…
Hyperbolic Manifold Regression
Gian Maria Marconi, Lorenzo Rosasco, Carlo Ciliberto
Geometric representation learning has recently shown great promise in several machine learning settings, ranging from relational learning to language processing and generative mode…
Manifold Structured Prediction
Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi +1
Structured prediction provides a general framework to deal with supervised problems where the outputs have semantically rich structure. While classical approaches consider finite,…