4 citations · 4 across the 9 of their papers we have counts for
13 papers
Humanoid Horizon: Extending Task Horizon in Whole-Body Loco-Manipulation via Parallel Training, Dynamic Starting, and Reward Gating
Haozhuo Zhang, Qiang Zhang, Jian Tang +4
Cluttered indoor environments, where large and heavy objects are scattered across diverse surfaces, require humanoid robots to sequentially navigate, grasp, transport, and accurate…
PROMO: Preference-conditioned Multi-Objective Reinforcement Learning for Quadrupedal Robots
Amr Mousa, Rifny Rachman, Neil Karavis +2
Quadrupedal locomotion requires balancing conflicting objectives such as command tracking, stability, and energy efficiency, yet conventional reinforcement learning (RL) hardcodes…
Should I stay or should I show? Learning to selectively disclose information
Carlotta Giacchetta, Alessando Bogani, Cesare Barbera +4
In many high-stakes settings, human decision-makers can acquire support information before making a decision. However, acquiring information is costly, and disclosure may fail to i…
CoCoNav: Conformal Control for Safe Robot Navigation in Crowds
Cheng Guo, Mingzhe Ni, Zheng Liang +5
Safe and efficient robot navigation in crowds requires anticipating pedestrian motion despite uncertain and potentially shifting prediction errors. Existing reactive methods can pr…
Beyond Prediction-Set Size: Quantifying Conformal Uncertainty through Credal Geometry
Siu Lun Chau, Soroush H. Zargarbashi, Yusuf Sale +1
Prediction-set size offers a coarse summary of conformal uncertainty. We develop a richer perspective through the geometry of credal sets: families of probability distributions com…
Adaptive Conformal Prediction for Quantum Machine Learning
Douglas Spencer, Samual Nicholls, Michele Caprio
Quantum machine learning seeks to leverage quantum computers to improve upon classical machine learning algorithms. Currently, robust uncertainty quantification methods remain unde…
PoseDiff: A Unified Diffusion Model Bridging Robot Pose Estimation and Video-to-Action Control
Haozhuo Zhang, Michele Caprio, Jing Shao +4
We present PoseDiff, a conditional diffusion model that unifies robot state estimation and control within a single framework. At its core, PoseDiff maps raw visual observations int…
When Do Credal Sets Stabilize? Fixed-Point Theorems for Credal Set Updates
Michele Caprio, Siu Lun Chau, Krikamol Muandet
Many machine learning algorithms rely on iterative updates of uncertainty representations, ranging from variational inference and expectation-maximization, to reinforcement learnin…
LHM-Humanoid: Long-Horizon Human Motion Control for Continuous Object Transport in Cluttered Scenes
Haozhuo Zhang, Jingkai Sun, Michele Caprio +5
Physics-based human motion control can make a simulated character walk, sit, and manipulate objects with high physical realism. Almost always, though, this happens in short, isolat…
A Category-Theoretic Analysis of Conformal Prediction
Michele Caprio
Conformal prediction (CP) produces prediction regions with finite-sample, distribution free coverage guarantees, but its interpretation as a quantitative uncertainty tool is often…
Epistemic Errors of Imperfect Multitask Learners When Distributions Shift
Sabina J. Sloman, Michele Caprio, Samuel Kaski
Uncertainty-aware machine learners, such as Bayesian neural networks, output a quantification of uncertainty instead of a point prediction. We provide uncertainty-aware learners wi…
Integral Imprecise Probability Metrics
Siu Lun Chau, Michele Caprio, Krikamol Muandet
Quantifying differences between probability distributions is fundamental to statistics and machine learning, primarily for comparing statistical uncertainty. In contrast, epistemic…
TAR: Teacher-Aligned Representations via Contrastive Learning for Quadrupedal Locomotion
Amr Mousa, Neil Karavis, Michele Caprio +2
Quadrupedal locomotion via Reinforcement Learning (RL) is commonly addressed using the teacher-student paradigm, where a privileged teacher guides a proprioceptive student policy.…