Claims Browser

Muon with exact-polar update may fail to converge, while Muon with finite Newton-Schulz can succeed

"Muon with the exact-polar update may fail to converge"

The sample complexity bounds for Muon match the best-known guarantees for nonsmooth nonconvex optimization and are optimal for smooth nonconvex optimization up to problem-dependent factors

"The resulting sample complexity bounds match the best-known guarantees for nonsmooth nonconvex optimization and are optimal for smooth nonconvex optimization up to problem-dependent factors."

Under finite second moments, minimizers exist for the weak GW framework and martingale gluing can recover an optimal coupling

"Under finite second moments, minimizers exist and martingale gluing recovers an optimal coupling."

Social interaction in collective learning can amplify early mistakes when credibility is generated by senders' decision processes

"Social interaction can improve collective learning but also amplify early mistakes."

Moderate transmission accelerates error correction in multi-agent learning systems, while strong transmission can lock populations into wrong consensus

"Monte Carlo experiments show the corresponding non-monotone performance pattern: moderate transmission accelerates correction, whereas strong transmission can lock populations into wrong consensus"

Confidence-sensitive transmission amplifies social error in reinforcement learning agents, while confidence-dependent private learning stabilizes it

"Ablations reveal a dual role for confidence: credibility-sensitive transmission amplifies social error, while confidence-dependent private learning stabilises it."

Low permeability between communities sustains disagreement in multi-agent systems

"low permeability instead sustains disagreement"

Existing minimax, primal-dual, and fitted fixed-point estimators for marginalized importance weighting can leave residual occupancy-balance violations due to function-class approximation, regularization, or incomplete optimization

"Existing minimax, primal-dual, and fitted fixed-point estimators can leave residual occupancy-balance violations because of function-class approximation, regularization, or incomplete optimization."

Anima Anandkumar is using AI to model physical world phenomena including weather and fusion reactors

"Now she's using it to model the physical world, from weather to fusion reactors."

Occupancy-balance violations in existing estimators are difficult to diagnose and reduce because objectives lack a direct supervised validation loss for hyperparameter tuning, model selection, and early stopping

"These violations are difficult to diagnose and reduce because the objectives generally lack a direct supervised validation loss for hyperparameter tuning, model selection, and early stopping."

Isotonic Bellman calibration is a one-dimensional, model-agnostic post-processing method that reduces occupancy-balance violations while preserving ranking information in occupancy-ratio estimates

"We introduce isotonic Bellman calibration, a one-dimensional, model-agnostic post-processing method that reduces these violations while preserving the ranking information in any initial occupancy-ratio estimate."

Isotonic Bellman calibration achieves small calibration error and KL risk within statistical error of the best monotone correction, with guarantees for downstream target-occupancy functionals including policy-value estimation

"isotonic Bellman calibration achieves small calibration error and KL risk within statistical error of the best monotone correction, with guarantees for downstream target-occupancy functionals, including policy-value estimation."

Any fitted ratio with small calibration error performs nearly as well as the best post-processing based on its fitted values, as shown by a calibration-refinement bound

"we derive a calibration-refinement bound showing that any fitted ratio with small calibration error performs nearly as well as the best post-processing based on its fitted values."

Computing Lipschitz constants is difficult even for shallow ReLU networks

"computing them is difficult even for shallow ReLU networks"

Maximizing the Lp-norm over a zonotope is W[1]-hard with respect to dimension for every fixed p in (1,∞) ∩ ℚ

"for every fixed $p\in (1,\infty)\cap \mathbb{Q}$, maximizing the $L_p$-norm over a zonotope in $\mathbb{R}^d$ is W[1]-hard with respect to the dimension $d$"

Brute-force enumeration algorithms are essentially optimal for zonotope norm maximization under the Exponential Time Hypothesis

"our hardness results imply that brute-force enumeration algorithms are essentially optimal for this problem under the Exponential Time Hypothesis"

The paper resolves an open problem posted at COLT'25 regarding parameterized complexity of zonotope norm maximization

"Our paper resolves an open problem posted at COLT'25"

The authors used LLMs as part of their research process

"we explicitly describe our research process including the use of LLMs"