Genre
Variational Annealing on Graphs for Combinatorial Optimization
We demonstrate that this assumption imposes performance limitations in particular on difficult problem instances.
Provable and Efficient Dataset Distillation for Kernel Ridge Regression
Our code is available at GitHub.
The Gain of Ordering in Online Learning
V ov95, CBL06] and online convex optimization [Haz16, Ora19] have been developed. Until the labels of all examples of X have been predicted: The learning algorithm picks a point x X and makes a prediction z R about its label.
Topological RANSAC for instance verification and retrieval without fine-tuning
To address these shortcomings, we introduce a pioneering technique that replaces the spatial model with a topological one within the RANSAC process.
SM3-Text-to-Query: Synthetic M ulti-M odel Medical Text-to-Query Benchmark
Text-to-Query systems have surprisingly not been investigated so far.
EDGI: Equivariant Diffusion for Planning with Embodied Agents Johann Brehmer Qualcomm AI Research
We integrate this model in a planning loop, where conditioning and classifier guidance let us softly break the symmetry for specific tasks as needed.
A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise
In this paper, we study the same problem in the Massart noise model that we now define.
Prediction and Control in Continual Reinforcement Learning
Deep reinforcement learning (RL) has achieved remarkable successes in complex tasks, e.g Go [