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For a finite $\mathbb{Z}$-algebra $R$, i.e., for a $\mathbb{Z}$-algebra which is a finitely generated $\mat…

We design and evaluate a Bayesian optimization framework for resource efficient pre-training of Transformer…

Autonomous shuttles (AS) operate in several cities and have shown potential to improve the public transport…

Many connections and dualities in representation theory can be explained using quasi-hereditary covers in t…

We discuss generalizations of the notions of projective transformations acting on affine model of Riemann-C…

Control theory is an important cornerstone of the robotics field and is considered a fundamental subject in…

Relational databases play an important role in this Big Data era. However, it is challenging for non-expert…

Video-grounded dialogue systems aim to integrate video understanding and dialogue understanding to generate…

This paper revisits the standard pretrain-then-finetune paradigm used in computer vision for visual recogni…

In this paper, we consider a planning problem for a hierarchical finite state machine (HFSM) and develop an…

We derive new constraints on axion-like particles (ALPs) using precision $X$-ray polarization studies of ma…

The phase behavior and structural properties of hard anisotropic particles (prisms and dumbbells) are exami…

For a complicated algorithm, its implementation by a human programmer usually starts with outlining a rough…

We verify that the recently proven infinite families of holographic entropy inequalities are maximally tigh…

This study introduces a new paradigm that unifies abrasion and breakage concepts, allowing for a holistic u…

Temporal reasoning is a crucial NLP task, providing a nuanced understanding of time-sensitive contexts with…

The closed-loop stability and infinite-horizon performance of receding-horizon approximations are studied f…

In this paper, we address the problem of distributed power allocation in a $K$ user fading multiple access …

The $2$-adic complexity has been well-analyzed in the periodic case. However, we are not aware of any theor…

This paper solves the continuous classification problem for finite clouds of unlabelled points under Euclid…

We present a general kernel-based framework for learning operators between Banach spaces along with a prior…

We aim to demonstrate in experiments that our cost sensitive PEGASOS SVM achieves good performance on imbal…

Probabilistic weather forecasting is critical for decision-making in high-impact domains such as flood fore…