20 papers · ranked by Valyu relevance
Jack Haines, Valerio Vitali, Kyle Bottrill, Pooja Uday Naik + 6 more
'Marco Gandolfi' 'Costantino De Angelis' 'Yohann Franz' 'Cosimo Lacava' 'Periklis Petropoulos' 'Massimiliano Guasoni'] Title: Abstract Compact power splitters are essential components in integrated optics. While 1 × 2 power splitters with uniform splitting are widely used, a 1 × N splitter with arbitrary number N of…
Huan Yuan, Jiagui Wu, Jinping Zhang, Xun Pu + 4 more
'Junbo Yang' 'Onofrio M. Maragò'] A series of reconfigurable compact photonic arbitrary power splitters are proposed based on the hybrid structure of silicon and Ge2Sb2Se4Te1 (GSST), which is a new kind of non-volatile optical phase change material (O-PCM) with low absorption. Our pixelated meta-hybrid has an extremely…
Gang Xu, Tianai Zhou, Xiu-Bo Chen, Xiaojun Wang + 1 more
Quantum information splitting (QIS) provides an idea for transmitting the quantum state through a classical channel and a preshared quantum entanglement resource. This paper presents a new scheme for QIS based on a five-qubit cluster state and a Bell state. In this scheme, the sender transmits the unknown three-qubit…
Xi He, Max A. Little
In this paper, we introduce a generic data structure called decision trees, which integrates several well-known data structures, including binary search trees, -D trees, binary space partition trees, and decision tree models from machine learning. We provide the first axiomatic definition of decision trees. These…
Elisabet Burjons, Peter Rossmanith
Given a subset of size k of a very large universe a randomized way to find this subset could consist of deleting half of the universe and then searching the remaining part. With a probability of 2 −k one will succeed. By probability amplification, a randomized algorithm needs about 2 k rounds until it succeeds. We…
Gabriel Ebner, Jasmin Blanchette, Sophie Tourret
AVATAR is an elegant and effective way to split clauses in a saturation prover using a SAT solver. But is it refutationally complete? And how does it relate to other splitting architectures? To answer these questions, we present a unifying framework that extends a saturation calculus (e.g., superposition) with…
Serge Cohen, Shambo Saha
We study sequences of partitions of a non decreasing sequence I n of intervals into subintervals, starting from the trivial partition, in which each partition is obtained from the one before by splitting its subintervals in two, according to a given rule, and then merging pairs of subintervals at the break points of…
Roman Joeres, David B. Blumenthal, Olga V. Kalinina
Information Leakage is an increasing problem in machine learning research. It is a common practice to report models with benchmarks, comparing them to the state-of-the-art performance on the test splits of datasets. If two or more dataset splits contain identical or highly similar samples, a model risks simply…
Shaked Tayouri, Vladislav Kogan, Jacob Beal, Tal Levy + 7 more
Biosecurity screening of synthetic DNA orders is a key defense against malicious actors and careless enthusiasts producing dangerous pathogens or toxins. It is important to evaluate biosecurity screening tools for potential vulnerabilities and to work responsibly with providers to ensure that vulnerabilities can be…
Authors not listed
The effectiveness of machine learning (ML) in drug discovery hinges on evaluation and modeling approaches that align with how compounds are tested and compared in real experimental contexts. We observe that experimental data in public repositories like ChEMBL naturally clusters by assay origin, while retaining…
Toby Dylan Hocking
Binary segmentation is the classic greedy algorithm which recursively splits a sequential data set by optimizing some loss or likelihood function. Binary segmentation is widely used for changepoint detection in data sets measured over space or time, and as a sub-routine for decision tree learning. In theory it should…
Warren James, Amelia R. Hunt, Alasdair D. F. Clarke
It is possible to accomplish multiple goals when available resources are abundant, but when the tasks are difficult and resources are limited, it is better to focus on one task and complete it successfully than to divide your efforts and fail on both. Previous research has shown that people rarely apply this logic when…
Timothy DeLise
Real-life machine learning problems exhibit distributional shifts in the data from one time to another or from one place to another. This behavior is beyond the scope of the traditional empirical risk minimization paradigm, which assumes i.i.d. distribution of data over time and across locations. The emerging field of…
Authors not listed
Today, machine learning models are employed extensively to predict the physicochemical and biological properties of molecules. Their performance is typically evaluated on in-distribution (ID) data, i.e., data originating from the same distribution as the training data. However, the real-world applications of such…
Laura Marras, Maxime Verwoert, Maarten C. Ottenhoff, Sophocles Goulis + 8 more
Ideally, decisions are made based on prior knowledge, which allows for informed choices. Real life, however, often requires us to make decisions arbitrarily, without sufficient information. Decoding decision making processes from neural activity could allow for cognitive neuroprostheses and Brain-Computer Interfaces…
Luc Devroye, Jad Hamdan
We propose a novel, simple density estimation algorithm for bounded monotone densities with compact support under a cellular restriction. We show that its expected error (L1 distance) converges at a rate of n −1/3 , that its expected runtime is sublinear and, in doing so, find a connection to the theory of…
Naomi Chaix-Eichel, Snigdha Dagar, Fréderic Alexandre, Thomas Boraud + 1 more
During the past decades, hippocampal formation has undergone extensive studies, leading researchers to identify a vast collection of cells with functional properties. Several investigations, supported by carefully crafted models, have examined the origin of such cells. The most recent models hypothesize that temporal…
Mert Özkan, Viola Störmer
Spatial attention enables us to select regions of space and prioritize visual processing at the attended locations. Previous research has shown that spatial attention can be flexibly tuned to broader or narrower regions in space, and in some cases be split amongst multiple locations. Here, we investigate how…
Trevor Gokey, David L. Mobley
Molecular mechanics force fields require a chemical perception model to assign parameters to molecules. A recent advancement in force fields is the use of the SMARTS substructure query language as the perception model. Although it is straightforward to write SMARTS patterns to define new force field parameters, it is…
Matthew Witman, Peter Schindler
Machine learning (ML) models in the materials sciences that are validated by overly simplistic cross-validation (CV) protocols can yield biased performance estimates for downstream modeling or materials screening tasks. This can be particularly counterproductive for applications where the time and cost of failed…