Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
1903.02073	Model Order Reduction for Temperature-Dependent Nonlinear Mechanical Systems: A Multiple Scales Approach	The thermal dynamics in thermo-mechanical systems exhibits a much slower time scale compared to the structural dynamics. In this work, we use the method of multiple scales to reduce the thermo-mechanical structural models with a slowly-varying temperature distribution in a systematic manner. In the process, we construc...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	123,409
2208.06224	Lattice Generalizations of the Concept of Fuzzy Numbers and Zadeh's Extension Principle	The concept of a fuzzy number is generalized to the case of a finite carrier set of partially ordered elements, more precisely, a lattice, when a membership function also takes values in a partially ordered set (a lattice). Zadeh's extension principle for determining the degree of membership of a function of fuzzy numb...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	312,646
2302.02408	Multi-View Masked World Models for Visual Robotic Manipulation	Visual robotic manipulation research and applications often use multiple cameras, or views, to better perceive the world. How else can we utilize the richness of multi-view data? In this paper, we investigate how to learn good representations with multi-view data and utilize them for visual robotic manipulation. Specif...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	343,990
2006.12453	Fanoos: Multi-Resolution, Multi-Strength, Interactive Explanations for Learned Systems	Machine learning is becoming increasingly important to control the behavior of safety and financially critical components in sophisticated environments, where the inability to understand learned components in general, and neural nets in particular, poses serious obstacles to their adoption. Explainability and interpret...	true	false	false	false	true	false	true	true	false	false	false	false	false	false	false	true	false	false	183,595
2003.11524	Automated Service Discovery for Social Internet-of-Things Systems	In this paper, we propose to design an automated service discovery process to allow mobile crowdsourcing task requesters select a small set of devices out of a large-scale Internet-of-things (IoT) network to execute their tasks. To this end, we proceed by dividing the large-scale IoT network into several virtual commun...	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	169,629
2211.16940	DiffPose: Toward More Reliable 3D Pose Estimation	Monocular 3D human pose estimation is quite challenging due to the inherent ambiguity and occlusion, which often lead to high uncertainty and indeterminacy. On the other hand, diffusion models have recently emerged as an effective tool for generating high-quality images from noise. Inspired by their capability, we expl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	333,801
1811.03601	Deep BV: A Fully Automated System for Brain Ventricle Localization and Segmentation in 3D Ultrasound Images of Embryonic Mice	Volumetric analysis of brain ventricle (BV) structure is a key tool in the study of central nervous system development in embryonic mice. High-frequency ultrasound (HFU) is the only non-invasive, real-time modality available for rapid volumetric imaging of embryos in utero. However, manual segmentation of the BV from H...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	112,882
2005.06318	A 28-nm Convolutional Neuromorphic Processor Enabling Online Learning with Spike-Based Retinas	In an attempt to follow biological information representation and organization principles, the field of neuromorphic engineering is usually approached bottom-up, from the biophysical models to large-scale integration in silico. While ideal as experimentation platforms for cognitive computing and neuroscience, bottom-up...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	176,976
1202.6037	Compressed Beamforming in Ultrasound Imaging	Emerging sonography techniques often require increasing the number of transducer elements involved in the imaging process. Consequently, larger amounts of data must be acquired and processed. The significant growth in the amounts of data affects both machinery size and power consumption. Within the classical sampling f...	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	14,601
2203.11572	Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and Simplicity	Despite significant progress, there remain three limitations to the previous multi-view clustering algorithms. First, they often suffer from high computational complexity, restricting their feasibility for large-scale datasets. Second, they typically fuse multi-view information via one-stage fusion, neglecting the poss...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	286,965
2410.06977	Adaptive High-Frequency Transformer for Diverse Wildlife Re-Identification	Wildlife ReID involves utilizing visual technology to identify specific individuals of wild animals in different scenarios, holding significant importance for wildlife conservation, ecological research, and environmental monitoring. Existing wildlife ReID methods are predominantly tailored to specific species, exhibiti...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	496,418
2002.01563	Discovery of Self-Assembling $\pi$-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation	Electronically-active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from $\pi$-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	162,679
1712.01817	Analyzing Large-Scale, Distributed and Uncertain Data	The exponential growth of data in current times and the demand to gain information and knowledge from the data present new challenges for database researchers. Known database systems and algorithms are no longer capable of effectively handling such large data sets. MapReduce is a novel programming paradigm for processi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	86,184
2206.09491	On the Limitations of Stochastic Pre-processing Defenses	Defending against adversarial examples remains an open problem. A common belief is that randomness at inference increases the cost of finding adversarial inputs. An example of such a defense is to apply a random transformation to inputs prior to feeding them to the model. In this paper, we empirically and theoretically...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	303,588
2311.01895	Enhancing search engine precision and user experience through sentiment-based polysemy resolution	With the proliferation of digital content and the need for efficient information retrieval, this study's insights can be applied to various domains, including news services, e-commerce, and digital marketing, to provide users with more meaningful and tailored experiences. The study addresses the common problem of polys...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	405,219
1908.01211	Word2vec to behavior: morphology facilitates the grounding of language in machines	Enabling machines to respond appropriately to natural language commands could greatly expand the number of people to whom they could be of service. Recently, advances in neural network-trained word embeddings have empowered non-embodied text-processing algorithms, and suggest they could be of similar utility for embodi...	false	false	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	140,702
2212.13163	MRTNet: Multi-Resolution Temporal Network for Video Sentence Grounding	Given an untrimmed video and natural language query, video sentence grounding aims to localize the target temporal moment in the video. Existing methods mainly tackle this task by matching and aligning semantics of the descriptive sentence and video segments on a single temporal resolution, while neglecting the tempora...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	338,233
2401.01023	CautionSuicide: A Deep Learning Based Approach for Detecting Suicidal Ideation in Real Time Chatbot Conversation	Suicide is recognized as one of the most serious concerns in the modern society. Suicide causes tragedy that affects countries, communities, and families. There are many factors that lead to suicidal ideations. Early detection of suicidal ideations can help to prevent suicide occurrence by providing the victim with the...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	419,194
1211.0963	Detecting, Representing and Querying Collusion in Online Rating Systems	Online rating systems are subject to malicious behaviors mainly by posting unfair rating scores. Users may try to individually or collaboratively promote or demote a product. Collaborating unfair rating 'collusion' is more damaging than individual unfair rating. Although collusion detection in general has been widely s...	true	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	19,567
2304.00466	Learning Robust Medical Image Segmentation from Multi-source Annotations	Collecting annotations from multiple independent sources could mitigate the impact of potential noises and biases from a single source, which is a common practice in medical image segmentation. Learning segmentation networks from multi-source annotations remains a challenge due to the uncertainties brought by the varia...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,698
2208.05163	Auto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization	Vision transformers (ViTs) are emerging with significantly improved accuracy in computer vision tasks. However, their complex architecture and enormous computation/storage demand impose urgent needs for new hardware accelerator design methodology. This work proposes an FPGA-aware automatic ViT acceleration framework ba...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	312,333
1806.04425	Ranking Robustness Under Adversarial Document Manipulations	For many queries in the Web retrieval setting there is an on-going ranking competition: authors manipulate their documents so as to promote them in rankings. Such competitions can have unwarranted effects not only in terms of retrieval effectiveness, but also in terms of ranking robustness. A case in point, rankings ca...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	100,229
2210.15379	MorphTE: Injecting Morphology in Tensorized Embeddings	In the era of deep learning, word embeddings are essential when dealing with text tasks. However, storing and accessing these embeddings requires a large amount of space. This is not conducive to the deployment of these models on resource-limited devices. Combining the powerful compression capability of tensor products...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	326,927
1903.04282	Grid-Constrained Distributed Optimization for Frequency Control with Low-Voltage Flexibility	Providing frequency control services with flexible assets connected to the low-voltage distribution grid, amongst which residential battery storage or electrical hot water boilers, can lead to congestion problems and voltage issues in the distribution grid. In order to mitigate these problems, a new regulation has been...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	123,947
1603.07886	A Novel Biologically Mechanism-Based Visual Cognition Model--Automatic Extraction of Semantics, Formation of Integrated Concepts and Re-selection Features for Ambiguity	Integration between biology and information science benefits both fields. Many related models have been proposed, such as computational visual cognition models, computational motor control models, integrations of both and so on. In general, the robustness and precision of recognition is one of the key problems for obje...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	53,685
2312.11797	Learning Merton's Strategies in an Incomplete Market: Recursive Entropy Regularization and Biased Gaussian Exploration	We study Merton's expected utility maximization problem in an incomplete market, characterized by a factor process in addition to the stock price process, where all the model primitives are unknown. We take the reinforcement learning (RL) approach to learn optimal portfolio policies directly by exploring the unknown ma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	416,716
2205.01053	Markov Abstractions for PAC Reinforcement Learning in Non-Markov Decision Processes	Our work aims at developing reinforcement learning algorithms that do not rely on the Markov assumption. We consider the class of Non-Markov Decision Processes where histories can be abstracted into a finite set of states while preserving the dynamics. We call it a Markov abstraction since it induces a Markov Decision ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	294,458
1601.03830	Ultra-Reliable Cloud Mobile Computing with Service Composition and Superposition Coding	An emerging requirement for 5G systems is the ability to provide wireless ultra-reliable communication (URC) services with close-to-full availability for cloud-based applications. Among such applications, a prominent role is expected to be played by mobile cloud computing (MCC), that is, by the offloading of computatio...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	50,955
2210.09465	Understanding CNN Fragility When Learning With Imbalanced Data	Convolutional neural networks (CNNs) have achieved impressive results on imbalanced image data, but they still have difficulty generalizing to minority classes and their decisions are difficult to interpret. These problems are related because the method by which CNNs generalize to minority classes, which requires impro...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	324,539
1809.00381	Multitask Learning for Fundamental Frequency Estimation in Music	Fundamental frequency (f0) estimation from polyphonic music includes the tasks of multiple-f0, melody, vocal, and bass line estimation. Historically these problems have been approached separately, and only recently, using learning-based approaches. We present a multitask deep learning architecture that jointly estimate...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	106,566
1911.04326	ASP-Core-2 Input Language Format	Standardization of solver input languages has been a main driver for the growth of several areas within knowledge representation and reasoning, fostering the exploitation in actual applications. In this document we present the ASP-Core-2 standard input language for Answer Set Programming, which has been adopted in ASP ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	152,963
1911.08303	Lightweight Residual Network for The Classification of Thyroid Nodules	Ultrasound is a useful technique for diagnosing thyroid nodules. Benign and malignant nodules that automatically discriminate in the ultrasound pictures can provide diagnostic recommendations or, improve diagnostic accuracy in the absence of specialists. The main issue here is how to collect suitable features for this ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	154,154
1905.09271	Infinite Grid Exploration by Disoriented Robots	We deal with a set of autonomous robots moving on an infinite grid. Those robots are opaque, have limited visibility capabilities, and run using synchronous Look-Compute-Move cycles. They all agree on a common chirality, but have no global compass. Finally, they may use lights of different colors, but except from that,...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	131,692
1606.09029	Geometry in Active Learning for Binary and Multi-class Image Segmentation	We propose an active learning approach to image segmentation that exploits geometric priors to speed up and streamline the annotation process. It can be applied for both background-foreground and multi-class segmentation tasks in 2D images and 3D image volumes. Our approach combines geometric smoothness priors in the i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	57,940
2205.08020	Partial Product Aware Machine Learning on DNA-Encoded Libraries	DNA encoded libraries (DELs) are used for rapid large-scale screening of small molecules against a protein target. These combinatorial libraries are built through several cycles of chemistry and DNA ligation, producing large sets of DNA-tagged molecules. Training machine learning models on DEL data has been shown to be...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	296,791
2310.00119	Fewshot learning on global multimodal embeddings for earth observation tasks	In this work we pretrain a CLIP/ViT based model using three different modalities of satellite imagery across five AOIs covering over ~10\% of Earth's total landmass, namely Sentinel 2 RGB optical imagery, Sentinel 1 SAR radar amplitude and interferometric coherence. This model uses $\sim 250$ M parameters. Then, we use...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	395,830
1809.04296	Data-driven repetitive control: Wind tunnel experiments under turbulent conditions	A commonly applied method to reduce the cost of wind energy, is alleviating the periodic loads on turbine blades using Individual Pitch Control (IPC). In this paper, a data-driven IPC methodology called Subspace Predictive Repetitive Control (SPRC) is employed. The effectiveness of SPRC will be demonstrated on a scaled...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	107,532
2402.06379	Learning using privileged information for segmenting tumors on digital mammograms	Limited amount of data and data sharing restrictions, due to GDPR compliance, constitute two common factors leading to reduced availability and accessibility when referring to medical data. To tackle these issues, we introduce the technique of Learning Using Privileged Information. Aiming to substantiate the idea, we a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	428,281
1909.10754	FEED: Feature-level Ensemble for Knowledge Distillation	Knowledge Distillation (KD) aims to transfer knowledge in a teacher-student framework, by providing the predictions of the teacher network to the student network in the training stage to help the student network generalize better. It can use either a teacher with high capacity or {an} ensemble of multiple teachers. How...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	146,624
2305.11435	Syllable Discovery and Cross-Lingual Generalization in a Visually Grounded, Self-Supervised Speech Model	In this paper, we show that representations capturing syllabic units emerge when training a self-supervised speech model with a visually-grounded training objective. We demonstrate that a nearly identical model architecture (HuBERT) trained with a masked language modeling loss does not exhibit this same ability, sugges...	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	365,525
2406.02716	Optimal Rates for $O(1)$-Smooth DP-SCO with a Single Epoch and Large Batches	In this paper we revisit the DP stochastic convex optimization (SCO) problem. For convex smooth losses, it is well-known that the canonical DP-SGD (stochastic gradient descent) achieves the optimal rate of $O\left(\frac{LR}{\sqrt{n}} + \frac{LR \sqrt{p \log(1/\delta)}}{\epsilon n}\right)$ under $(\epsilon, \delta)$-DP,...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	460,903
2004.10698	AutoEG: Automated Experience Grafting for Off-Policy Deep Reinforcement Learning	Deep reinforcement learning (RL) algorithms frequently require prohibitive interaction experience to ensure the quality of learned policies. The limitation is partly because the agent cannot learn much from the many low-quality trials in early learning phase, which results in low learning rate. Focusing on addressing t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	173,703
2304.06729	Meta-Learned Models of Cognition	Meta-learning is a framework for learning learning algorithms through repeated interactions with an environment as opposed to designing them by hand. In recent years, this framework has established itself as a promising tool for building models of human cognition. Yet, a coherent research program around meta-learned mo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	358,085
2205.00617	A high-order deferred correction method for the solution of free boundary problems using penalty iteration, with an application to American option pricing	This paper presents a high-order deferred correction algorithm combined with penalty iteration for solving free and moving boundary problems, using a fourth-order finite difference method. Typically, when free boundary problems are solved on a fixed computational grid, the order of the solution is low due to the discon...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	294,318
2310.04698	Tree-GPT: Modular Large Language Model Expert System for Forest Remote Sensing Image Understanding and Interactive Analysis	This paper introduces a novel framework, Tree-GPT, which incorporates Large Language Models (LLMs) into the forestry remote sensing data workflow, thereby enhancing the efficiency of data analysis. Currently, LLMs are unable to extract or comprehend information from images and may generate inaccurate text due to a lack...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	397,774
2109.11796	Edge but not Least: Cross-View Graph Pooling	Graph neural networks have emerged as a powerful model for graph representation learning to undertake graph-level prediction tasks. Various graph pooling methods have been developed to coarsen an input graph into a succinct graph-level representation through aggregating node embeddings obtained via graph convolution. H...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	257,061
2208.14372	Dead-beat model predictive control for discrete-time linear systems	In this paper, model predictive control (MPC) strategies are proposed for dead-beat control of linear systems with and without state and control constraints. In unconstrained MPC, deadbeat performance can be guaranteed by setting the control horizon to the system dimension, and adding an terminal equality constraint. I...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	315,302
1406.5298	Semi-Supervised Learning with Deep Generative Models	The ever-increasing size of modern data sets combined with the difficulty of obtaining label information has made semi-supervised learning one of the problems of significant practical importance in modern data analysis. We revisit the approach to semi-supervised learning with generative models and develop new models th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	34,018
2309.03837	Cross-Task Attention Network: Improving Multi-Task Learning for Medical Imaging Applications	Multi-task learning (MTL) is a powerful approach in deep learning that leverages the information from multiple tasks during training to improve model performance. In medical imaging, MTL has shown great potential to solve various tasks. However, existing MTL architectures in medical imaging are limited in sharing infor...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	390,527
2104.10429	Portfolio Search and Optimization for General Strategy Game-Playing	Portfolio methods represent a simple but efficient type of action abstraction which has shown to improve the performance of search-based agents in a range of strategy games. We first review existing portfolio techniques and propose a new algorithm for optimization and action-selection based on the Rolling Horizon Evolu...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	231,582
2303.07847	Transfer Learning for Real-time Deployment of a Screening Tool for Depression Detection Using Actigraphy	Automated depression screening and diagnosis is a highly relevant problem today. There are a number of limitations of the traditional depression detection methods, namely, high dependence on clinicians and biased self-reporting. In recent years, research has suggested strong potential in machine learning (ML) based met...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	351,406
2306.01424	Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model	Counterfactual inference aims to answer retrospective "what if" questions and thus belongs to the most fine-grained type of inference in Pearl's causality ladder. Existing methods for counterfactual inference with continuous outcomes aim at point identification and thus make strong and unnatural assumptions about the u...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	370,449
2405.16224	Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning	Graph contrastive learning (GCL), standing as the dominant paradigm in the realm of graph pre-training, has yielded considerable progress. Nonetheless, its capacity for out-of-distribution (OOD) generalization has been relatively underexplored. In this work, we point out that the traditional optimization of InfoNCE in ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	457,315
1303.4845	On Constructing the Value Function for Optimal Trajectory Problem and its Application to Image Processing	We proposed an algorithm for solving Hamilton-Jacobi equation associated to an optimal trajectory problem for a vehicle moving inside the pre-specified domain with the speed depending upon the direction of the motion and current position of the vehicle. The dynamics of the vehicle is defined by an ordinary differential...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	23,039
2105.14464	Comparison-limited Vector Quantization	In this paper a variation of the classic vector quantization problem is considered. In the standard formulation, a quantizer is designed to minimize the distortion between input and output when the number of reconstruction points is fixed. We consider, instead, the scenario in which the number of comparators used in qu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	237,685
1308.5038	Group-Sparse Signal Denoising: Non-Convex Regularization, Convex Optimization	Convex optimization with sparsity-promoting convex regularization is a standard approach for estimating sparse signals in noise. In order to promote sparsity more strongly than convex regularization, it is also standard practice to employ non-convex optimization. In this paper, we take a third approach. We utilize a no...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	26,592
1605.02215	Formation of subject area and the co-authors network by sounding of Google Scholar Citations service	The suggested methodic is the way of formatting the subject areas models and co-authors networks by sounding the content networks. The paper represents the notion networks which match tags and authors of Google Scholar Citations service. Models depicted in the work were built for the physical optics area, and it can be...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	55,595
1405.1958	A Self-Adaptive Network Protection System	In this treatise we aim to build a hybrid network automated (self-adaptive) security threats discovery and prevention system; by using unconventional techniques and methods, including fuzzy logic and biological inspired algorithms under the context of soft computing.	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	true	false	false	32,934
2106.09146	Contrastive Reinforcement Learning of Symbolic Reasoning Domains	Abstract symbolic reasoning, as required in domains such as mathematics and logic, is a key component of human intelligence. Solvers for these domains have important applications, especially to computer-assisted education. But learning to solve symbolic problems is challenging for machine learning algorithms. Existing ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	241,553
2103.12797	RPT: Effective and Efficient Retrieval of Program Translations from Big Code	Program translation is a growing demand in software engineering. Manual program translation requires programming expertise in source and target language. One way to automate this process is to make use of the big data of programs, i.e., Big Code. In particular, one can search for program translations in Big Code. Howev...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	226,283
2307.13950	Deep Robust Multi-Robot Re-localisation in Natural Environments	The success of re-localisation has crucial implications for the practical deployment of robots operating within a prior map or relative to one another in real-world scenarios. Using single-modality, place recognition and localisation can be compromised in challenging environments such as forests. To address this, we pr...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	381,760
2009.00859	ALEX: Active Learning based Enhancement of a Model's Explainability	An active learning (AL) algorithm seeks to construct an effective classifier with a minimal number of labeled examples in a bootstrapping manner. While standard AL heuristics, such as selecting those points for annotation for which a classification model yields least confident predictions, there has been no empirical i...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	194,161
2106.05214	Implicit field learning for unsupervised anomaly detection in medical images	We propose a novel unsupervised out-of-distribution detection method for medical images based on implicit fields image representations. In our approach, an auto-decoder feed-forward neural network learns the distribution of healthy images in the form of a mapping between spatial coordinates and probabilities over a pro...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	240,010
2203.03985	SimpleTrack: Rethinking and Improving the JDE Approach for Multi-Object Tracking	Joint detection and embedding (JDE) based methods usually estimate bounding boxes and embedding features of objects with a single network in Multi-Object Tracking (MOT). In the tracking stage, JDE-based methods fuse the target motion information and appearance information by applying the same rule, which could fail whe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	284,307
1702.08896	Hierarchical Implicit Models and Likelihood-Free Variational Inference	Implicit probabilistic models are a flexible class of models defined by a simulation process for data. They form the basis for theories which encompass our understanding of the physical world. Despite this fundamental nature, the use of implicit models remains limited due to challenges in specifying complex latent stru...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	69,086
2411.07955	How To Discover Short, Shorter, and the Shortest Proofs of Unsatisfiability: A Branch-and-Bound Approach for Resolution Proof Length Minimization	Modern software for propositional satisfiability problems gives a powerful automated reasoning toolkit, capable of outputting not only a satisfiable/unsatisfiable signal but also a justification of unsatisfiability in the form of resolution proof (or a more expressive proof), which is commonly used for verification pur...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	507,731
1807.07982	Visitors to urban greenspace have higher sentiment and lower negativity on Twitter	With more people living in cities, we are witnessing a decline in exposure to nature. A growing body of research has demonstrated an association between nature contact and improved mood. Here, we used Twitter and the Hedonometer, a world analysis tool, to investigate how sentiment, or the estimated happiness of the wor...	false	false	false	true	false	false	false	false	true	false	false	false	false	true	false	false	false	false	103,427
1601.07024	Asymptotic analysis of downlink MIMO systems over Rician fading channels	In this work, we focus on the ergodic sum rate in the downlink of a single-cell large-scale multi-user MIMO system in which the base station employs N antennas to communicate with $K$ single-antenna user equipments. A regularized zero-forcing (RZF) scheme is used for precoding under the assumption that each link forms ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,372
2405.16760	Graphon Particle Systems, Part I: Spatio-Temporal Approximation and Law of Large Numbers	We study a class of graphon particle systems with time-varying random coefficients. In a graphon particle system, the interactions among particles are characterized by the coupled mean field terms through an underlying graphon and the randomness of the coefficients comes from the stochastic processes associated with th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	457,588
2107.04309	Understanding surrogate explanations: the interplay between complexity, fidelity and coverage	This paper analyses the fundamental ingredients behind surrogate explanations to provide a better understanding of their inner workings. We start our exposition by considering global surrogates, describing the trade-off between complexity of the surrogate and fidelity to the black-box being modelled. We show that trans...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	245,421
1304.6528	Nonanticipative Rate Distortion Function for General Source-Channel Matching	In this paper we invoke a nonanticipative information Rate Distortion Function (RDF) for sources with memory, and we analyze its importance in probabilistic matching of the source to the channel so that transmission of a symbol-by-symbol code with memory without anticipation is optimal, with respect to an average disto...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	24,180
2406.14761	Diffusion-Based Failure Sampling for Cyber-Physical Systems	Validating safety-critical autonomous systems in high-dimensional domains such as robotics presents a significant challenge. Existing black-box approaches based on Markov chain Monte Carlo may require an enormous number of samples, while methods based on importance sampling often rely on simple parametric families that...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	466,451
2009.02795	Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines	We use pretrained transformer-based language models in SemEval-2020 Task 7: Assessing the Funniness of Edited News Headlines. Inspired by the incongruity theory of humor, we use a contrastive approach to capture the surprise in the edited headlines. In the official evaluation, our system gets 0.531 RMSE in Subtask 1, 1...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	194,661
2307.06065	Operational Support Estimator Networks	In this work, we propose a novel approach called Operational Support Estimator Networks (OSENs) for the support estimation task. Support Estimation (SE) is defined as finding the locations of non-zero elements in sparse signals. By its very nature, the mapping between the measurement and sparse signal is a non-linear o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	378,954
1503.04768	Self-organizing Networks of Information Gathering Cognitive Agents	In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper we presen...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	41,182
2010.09309	Evolutionary Algorithm and Multifactorial Evolutionary Algorithm on Clustered Shortest-Path Tree problem	In literature, Clustered Shortest-Path Tree Problem (CluSPT) is an NP-hard problem. Previous studies often search for an optimal solution in relatively large space. To enhance the performance of the search process, two approaches are proposed: the first approach seeks for solutions as a set of edges. From the original ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	201,489
1705.10408	Distributed Time Synchronization for Networks with Random Delays and Measurement Noise	In this paper a new distributed asynchronous algorithm is proposed for time synchronization in networks with random communication delays, measurement noise and communication dropouts. Three different types of the drift correction algorithm are introduced, based on different kinds of local time increments. Under nonrest...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	74,383
2304.08384	Unsupervised Image Denoising with Score Function	Though achieving excellent performance in some cases, current unsupervised learning methods for single image denoising usually have constraints in applications. In this paper, we propose a new approach which is more general and applicable to complicated noise models. Utilizing the property of score function, the gradie...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	358,694
2106.06143	Monotonic Neural Network: combining Deep Learning with Domain Knowledge for Chiller Plants Energy Optimization	In this paper, we are interested in building a domain knowledge based deep learning framework to solve the chiller plants energy optimization problems. Compared to the hotspot applications of deep learning (e.g. image classification and NLP), it is difficult to collect enormous data for deep network training in real-wo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	240,377
2312.07598	Differential Equation Approximations for Population Games using Elementary Probability	Population games model the evolution of strategic interactions among a large number of uniform agents. Due to the agents' uniformity and quantity, their aggregate strategic choices can be approximated by the solutions of a class of ordinary differential equations. This mean-field approach has found to be an effective t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	true	414,989
2311.14651	History Filtering in Imperfect Information Games: Algorithms and Complexity	Historically applied exclusively to perfect information games, depth-limited search with value functions has been key to recent advances in AI for imperfect information games. Most prominent approaches with strong theoretical guarantees require subgame decomposition - a process in which a subgame is computed from publi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	410,183
2110.05802	Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking Platform	Obtaining standardized crowdsourced benchmark of computational methods is a major issue in data science communities. Dedicated frameworks enabling fair benchmarking in a unified environment are yet to be developed. Here we introduce Codabench, an open-source, community-driven platform for benchmarking algorithms or sof...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	260,408
1706.05983	Mixture-based Modeling of Spatially Correlated Interference in a Poisson Field of Interferers	As the interference in PPP based wireless networks exhibit spatial correlation, any joint analysis involving multiple spatial points either end up with numerical integrations over $\mathbb{R}^2$ or become analytically too intractable. To tackle these issues, we present an alternate approach which not only offers a simp...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	75,604
2403.20279	LUQ: Long-text Uncertainty Quantification for LLMs	Large Language Models (LLMs) have demonstrated remarkable capability in a variety of NLP tasks. However, LLMs are also prone to generate nonfactual content. Uncertainty Quantification (UQ) is pivotal in enhancing our understanding of a model's confidence on its generation, thereby aiding in the mitigation of nonfactual...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	442,690
2310.05720	HyperLips: Hyper Control Lips with High Resolution Decoder for Talking Face Generation	Talking face generation has a wide range of potential applications in the field of virtual digital humans. However, rendering high-fidelity facial video while ensuring lip synchronization is still a challenge for existing audio-driven talking face generation approaches. To address this issue, we propose HyperLips, a tw...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	398,267
2006.14835	Recovery of Binary Sparse Signals from Structured Biased Measurements	In this paper we study the reconstruction of binary sparse signals from partial random circulant measurements. We show that the reconstruction via the least-squares algorithm is as good as the reconstruction via the usually used program basis pursuit. We further show that we need as many measurements to recover an $s$-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	184,348
2408.10072	FFAA: Multimodal Large Language Model based Explainable Open-World Face Forgery Analysis Assistant	The rapid advancement of deepfake technologies has sparked widespread public concern, particularly as face forgery poses a serious threat to public information security. However, the unknown and diverse forgery techniques, varied facial features and complex environmental factors pose significant challenges for face for...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	481,705
1408.3081	Human Activity Learning and Segmentation using Partially Hidden Discriminative Models	Learning and understanding the typical patterns in the daily activities and routines of people from low-level sensory data is an important problem in many application domains such as building smart environments, or providing intelligent assistance. Traditional approaches to this problem typically rely on supervised lea...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	35,344
2301.07823	Resilient Containment Control of Heterogeneous Multi-Agent Systems Against Unbounded Sensor and Actuator Attacks	Accurate local state measurement is important to ensure the reliable operation of distributed multi-agent systems (MAS). Existing fault-tolerant control strategies generally assume the sensor faults to be bounded and uncorrelated. In this paper, we study the ramifications of allowing the sensor attack injections to be ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	341,016
2012.14756	Dialogue Response Selection with Hierarchical Curriculum Learning	We study the learning of a matching model for dialogue response selection. Motivated by the recent finding that models trained with random negative samples are not ideal in real-world scenarios, we propose a hierarchical curriculum learning framework that trains the matching model in an "easy-to-difficult" scheme. Our ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	213,598
1910.13911	Real-time Convolutional Networks for Depth-based Human Pose Estimation	We propose to combine recent Convolutional Neural Networks (CNN) models with depth imaging to obtain a reliable and fast multi-person pose estimation algorithm applicable to Human Robot Interaction (HRI) scenarios. Our hypothesis is that depth images contain less structures and are easier to process than RGB images whi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	151,511
2405.04215	NL2Plan: Robust LLM-Driven Planning from Minimal Text Descriptions	Today's classical planners are powerful, but modeling input tasks in formats such as PDDL is tedious and error-prone. In contrast, planning with Large Language Models (LLMs) allows for almost any input text, but offers no guarantees on plan quality or even soundness. In an attempt to merge the best of these two approac...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	452,488
2112.08968	Automated segmentation of 3-D body composition on computed tomography	Purpose: To develop and validate a computer tool for automatic and simultaneous segmentation of body composition depicted on computed tomography (CT) scans for the following tissues: visceral adipose (VAT), subcutaneous adipose (SAT), intermuscular adipose (IMAT), skeletal muscle (SM), and bone. Approach: A cohort of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	271,993
1607.07602	OntoCat: Automatically categorizing knowledge in API Documentation	Most application development happens in the context of complex APIs; reference documentation for APIs has grown tremendously in variety, complexity, and volume, and can be difficult to navigate. There is a growing need to develop well-organized ways to access the knowledge latent in the documentation; several research ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	59,046
2501.19178	No Foundations without Foundations -- Why semi-mechanistic models are essential for regulatory biology	Despite substantial efforts, deep learning has not yet delivered a transformative impact on elucidating regulatory biology, particularly in the realm of predicting gene expression profiles. Here, we argue that genuine "foundation models" of regulatory biology will remain out of reach unless guided by frameworks that in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	529,044
2405.15677	SMART: Scalable Multi-agent Real-time Motion Generation via Next-token Prediction	Data-driven autonomous driving motion generation tasks are frequently impacted by the limitations of dataset size and the domain gap between datasets, which precludes their extensive application in real-world scenarios. To address this issue, we introduce SMART, a novel autonomous driving motion generation paradigm tha...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	457,044
2003.06746	Beyond without Forgetting: Multi-Task Learning for Classification with Disjoint Datasets	Multi-task Learning (MTL) for classification with disjoint datasets aims to explore MTL when one task only has one labeled dataset. In existing methods, for each task, the unlabeled datasets are not fully exploited to facilitate this task. Inspired by semi-supervised learning, we use unlabeled datasets with pseudo labe...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	168,214
1202.1523	Information Forests	We describe Information Forests, an approach to classification that generalizes Random Forests by replacing the splitting criterion of non-leaf nodes from a discriminative one -- based on the entropy of the label distribution -- to a generative one -- based on maximizing the information divergence between the class-con...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	14,202
2005.06503	Generating collection transformations from proofs	Nested relations, built up from atomic types via product and set types, form a rich data model. Over the last decades the nested relational calculus, NRC, has emerged as a standard language for defining transformations on nested collections. NRC is a strongly-typed functional language which allows building up transform...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	177,011
2110.03689	DeepECMP: Predicting Extracellular Matrix Proteins using Deep Learning	Introduction: The extracellular matrix (ECM) is a networkof proteins and carbohydrates that has a structural and bio-chemical function. The ECM plays an important role in dif-ferentiation, migration and signaling. Several studies havepredicted ECM proteins using machine learning algorithmssuch as Random Forests, K-near...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	259,595

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.