We study spectral behavior of sparsely connected random networks under the random matrix framework. Sub-networks without any connection among them form a network having perfect community structure. As connections among the sub-networks are introduc...
Welcome back to your official /r/NFL Power Rankings! 8 years ago, when /r/NFL was just a baby, these rankings began and as the sub has grown, we have been proud to remain one of it's most popular fixt...
These are the association rankings for the 2024-25 season. The current season rankings are available here.
Product ranking is the core problem for revenue-maximizing online retailers. To design proper product ranking algorithms, various consumer choice models are proposed to characterize the consumers' behaviors when they are provided with a list of produ...
I ran an HVAC company for 24 years and exited debt-free. Here’s the business stuff nobody teaches you. I started my company in 1994 with $3,200. No financing, no partner, no safety net. Ran it 24 y...
We show that an amenable Invariant Random Subgroup of a locally compact second countable group lives in the amenable radical. This answers a question raised in the introduction of the paper "Kesten's Theorem for Invariant Random Subgroup" by Abert, G...
We introduce the DROW detector, a deep learning based detector for 2D range data. Laser scanners are lighting invariant, provide accurate range data, and typically cover a large field of view, making them interesting sensors for robotics applications...
Understand factors that determine local ranking Important: There's no way to request or pay for a better local ranking on Google. We do our best to keep the search algorithm details confidential to make …
Passive range of motion (or PROM) - Therapist or equipment moves the joint through the range of motion with no effort from the patient. Active assistive range of motion (or AAROM) - Patient uses the …
The set of visited sites and the number of visited sites are two basic properties of the random walk trajectory. We consider two independent random walks on a hyper-cubic lattice and study ordering probabilities associated with these characteristics....
Very recently, a fundamental observable has been introduced and analyzed to quantify the exploration of random walks: the time $τ_k$ required for a random walk to find a site that it never visited previously, when the walk has already visited $k$ di...
We propose a new strategy to identify the impact of class rank, exploiting a "visible" primary school rank from teachers' exam grades, and an "invisible" rank from unreported standardized test scores. Leveraging a unique panel dataset on Italian stud...
This paper presents a new framework for jointly enhancing the resolution and the dynamic range of an image, i.e., simultaneous super-resolution (SR) and high dynamic range imaging (HDRI), based on a convolutional neural network (CNN). From the common...
We analyze the low-energy e-N2 collisions within the framework of the Modified-Effective Range Theory (MERT) for the long-range potentials, developed by O'Malley, Spruch and Rosenberg [Journal of Math. Phys. 2, 491 (1961)]. In comparison to the tra...
The two parallel concepts of "small" sets of the real line are meagre sets and null sets. Those are equivalent to Cohen forcing and Random real forcing for $\aleph^{\aleph_0}_0$; in spite of this similarity, the Cohen forcing and Random Real forcing...
Returns unique rows in the provided source range, discarding duplicates. Rows are returned in the order in which they first appear in the source range. Parts of a UNIQUE function UNIQUE (range, by_co
Despite its compactness and information integrity, the range view representation of LiDAR data rarely occurs as the first choice for 3D perception tasks. In this work, we further push the envelop of the range-view representation with a novel multi-ta...
Passive range of motion (or PROM) - Therapist or equipment moves the joint through the range of motion with no effort from the patient. Active assistive range of motion (or AAROM) - Patient uses the …
In recent years, Parameter-Efficient Fine-Tuning (PEFT) methods like Low-Rank Adaptation (LoRA) have significantly enhanced the adaptability of large-scale pre-trained models. Weight-Decomposed Low-Rank Adaptation (DoRA) improves upon LoRA by separat...
This paper introduces Bayesian Hierarchical Low-Rank Adaption (BoRA), a novel method for finetuning multi-task Large Language Models (LLMs). Current finetuning approaches, such as Low-Rank Adaption (LoRA), perform exeptionally well in reducing traini...