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
2305.14376	PTGB: Pre-Train Graph Neural Networks for Brain Network Analysis	The human brain is the central hub of the neurobiological system, controlling behavior and cognition in complex ways. Recent advances in neuroscience and neuroimaging analysis have shown a growing interest in the interactions between brain regions of interest (ROIs) and their impact on neural development and disorder d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	367,003
2002.02667	Automated Lane Change Strategy using Proximal Policy Optimization-based Deep Reinforcement Learning	Lane-change maneuvers are commonly executed by drivers to follow a certain routing plan, overtake a slower vehicle, adapt to a merging lane ahead, etc. However, improper lane change behaviors can be a major cause of traffic flow disruptions and even crashes. While many rule-based methods have been proposed to solve lan...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	162,993
0705.0751	Approximate textual retrieval	An approximate textual retrieval algorithm for searching sources with high levels of defects is presented. It considers splitting the words in a query into two overlapping segments and subsequently building composite regular expressions from interlacing subsets of the segments. This procedure reduces the probability of...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	159
1901.11459	Funnelling: A New Ensemble Method for Heterogeneous Transfer Learning and its Application to Cross-Lingual Text Classification	Cross-lingual Text Classification (CLC) consists of automatically classifying, according to a common set C of classes, documents each written in one of a set of languages L, and doing so more accurately than when naively classifying each document via its corresponding language-specific classifier. In order to obtain an...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	120,263
2308.03539	DNFOMP: Dynamic Neural Field Optimal Motion Planner for Navigation of Autonomous Robots in Cluttered Environment	Motion planning in dynamically changing environments is one of the most complex challenges in autonomous driving. Safety is a crucial requirement, along with driving comfort and speed limits. While classical sampling-based, lattice-based, and optimization-based planning methods can generate smooth and short paths, they...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	384,073
2202.02144	Proceedings 10th International Workshop on Theorem Proving Components for Educational Software	This EPTCS volume contains the proceedings of the ThEdu'21 workshop, promoted on 11 July 2021, as a satellite event of CADE-28. Due to the COVID-19 pandemic, CADE-28 and all its co-located events happened as virtual events. ThEdu'21 was a vibrant workshop, with an invited talk by Gilles Dowek (ENS Paris-Saclay), eleven...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	278,710
2401.14085	Enhanced Multi-Target Tracking in Dynamic Environments: Distributed Control Methods Within the Random Finite Set Framework	Tracking multiple targets in dynamic environments using distributed sensor networks is a challenging problem that has received significant attention in recent years. In such scenarios, the network of sensors must coordinate their actions to estimate the locations and trajectories of multiple targets accurately. Multi-s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	423,966
2411.05222	Don't Look Twice: Faster Video Transformers with Run-Length Tokenization	Transformers are slow to train on videos due to extremely large numbers of input tokens, even though many video tokens are repeated over time. Existing methods to remove such uninformative tokens either have significant overhead, negating any speedup, or require tuning for different datasets and examples. We present Ru...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	506,581
2308.09523	Denoising Diffusion for 3D Hand Pose Estimation from Images	Hand pose estimation from a single image has many applications. However, approaches to full 3D body pose estimation are typically trained on day-to-day activities or actions. As such, detailed hand-to-hand interactions are poorly represented, especially during motion. We see this in the failure cases of techniques such...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	386,328
2408.12154	Binary codes from subset inclusion matrices	In this paper, we study the minimum distances of binary linear codes with parity check matrices formed from subset inclusion matrices $W_{t,n,k}$, representing $t$-element subsets versus $k$-element subsets of an $n$-element set. We provide both lower and upper bounds on the minimum distances of these codes and determi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	482,616
2405.09496	ParaNames 1.0: Creating an Entity Name Corpus for 400+ Languages using Wikidata	We introduce ParaNames, a massively multilingual parallel name resource consisting of 140 million names spanning over 400 languages. Names are provided for 16.8 million entities, and each entity is mapped from a complex type hierarchy to a standard type (PER/LOC/ORG). Using Wikidata as a source, we create the largest r...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	454,418
1902.08727	Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach	In unsupervised domain adaptation, it is widely known that the target domain error can be provably reduced by having a shared input representation that makes the source and target domains indistinguishable from each other. Very recently it has been studied that not just matching the marginal input distributions, but th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	122,258
1911.05381	Searching for Anomalies over Composite Hypotheses	The problem of detecting anomalies in multiple processes is considered. We consider a composite hypothesis case, in which the measurements drawn when observing a process follow a common distribution with an unknown parameter (vector), whose value lies in normal or abnormal parameter spaces, depending on its state. The ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	153,245
2311.11126	Bayesian Neural Networks: A Min-Max Game Framework	In deep learning, Bayesian neural networks (BNN) provide the role of robustness analysis, and the minimax method is used to be a conservative choice in the traditional Bayesian field. In this paper, we study a conservative BNN with the minimax method and formulate a two-player game between a deterministic neural networ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	408,808
2411.12670	Reconstructing Graph Signals from Noisy Dynamical Samples	We investigate the dynamical sampling space-time trade-off problem within a graph setting. Specifically, we derive necessary and sufficient conditions for space-time sampling that enable the reconstruction of an initial band-limited signal on a graph. Additionally, we develop and test numerical algorithms for approxima...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	509,492
1304.2994	A Generalized Online Mirror Descent with Applications to Classification and Regression	Online learning algorithms are fast, memory-efficient, easy to implement, and applicable to many prediction problems, including classification, regression, and ranking. Several online algorithms were proposed in the past few decades, some based on additive updates, like the Perceptron, and some on multiplicative update...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	23,782
2105.00074	Flow-Packet Hybrid Traffic Classification for Class-Aware Network Routing	Network traffic classification using machine learning techniques has been widely studied. Most existing schemes classify entire traffic flows, but there are major limitations to their practicality. At a network router, the packets need to be processed with minimum delay, so the classifier cannot wait until the end of t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	233,077
2405.02061	Towards general deep-learning-based tree instance segmentation models	The segmentation of individual trees from forest point clouds is a crucial task for downstream analyses such as carbon sequestration estimation. Recently, deep-learning-based methods have been proposed which show the potential of learning to segment trees. Since these methods are trained in a supervised way, the questi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	451,610
2105.06238	Multi-scale Regional Attention Deeplab3+: Multiple Myeloma Plasma Cells Segmentation in Microscopic Images	Multiple myeloma cancer is a type of blood cancer that happens when the growth of abnormal plasma cells becomes out of control in the bone marrow. There are various ways to diagnose multiple myeloma in bone marrow such as complete blood count test (CBC) or counting myeloma plasma cell in aspirate slide images using man...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	235,062
2208.14230	A Generic Algorithm for Top-K On-Shelf Utility Mining	On-shelf utility mining (OSUM) is an emerging research direction in data mining. It aims to discover itemsets that have high relative utility in their selling time period. Compared with traditional utility mining, OSUM can find more practical and meaningful patterns in real-life applications. However, there is a major ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	315,261
1903.03910	Fairness for Robust Log Loss Classification	Developing classification methods with high accuracy that also avoid unfair treatment of different groups has become increasingly important for data-driven decision making in social applications. Many existing methods enforce fairness constraints on a selected classifier (e.g., logistic regression) by directly forming ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	123,853
1910.04176	A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification	New conversation topics and functionalities are constantly being added to conversational AI agents like Amazon Alexa and Apple Siri. As data collection and annotation is not scalable and is often costly, only a handful of examples for the new functionalities are available, which results in poor generalization performan...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	148,694
1702.05860	Robust Sparse Estimation Tasks in High Dimensions	In this paper we initiate the study of whether or not sparse estimation tasks can be performed efficiently in high dimensions, in the robust setting where an $\eps$-fraction of samples are corrupted adversarially. We study the natural robust version of two classical sparse estimation problems, namely, sparse mean estim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	68,487
2412.01937	Approximately Optimal Search on a Higher-dimensional Sliding Puzzle	Higher-dimensional sliding puzzles are constructed on the vertices of a $d$-dimensional hypercube, where $2^d-l$ vertices are distinctly coloured. Rings with the same colours are initially set randomly on the vertices of the hypercube. The goal of the puzzle is to move each of the $2^d-l$ rings to pre-defined target ve...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	true	513,313
2502.12001	Merging Language and Domain Specific Models: The Impact on Technical Vocabulary Acquisition	This paper investigates the integration of technical vocabulary in merged language models. We explore the knowledge transfer mechanisms involved when combining a general-purpose language-specific model with a domain-specific model, focusing on the resulting model's comprehension of technical jargon. Our experiments ana...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	534,638
2405.15349	Everything is Editable: Extend Knowledge Editing to Unstructured Data in Large Language Models	Recent knowledge editing methods have primarily focused on modifying structured knowledge in large language models. However, this task setting overlooks the fact that a significant portion of real-world knowledge is stored in an unstructured format, characterized by long-form content, noise, and a complex yet comprehen...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	456,887
2005.07007	Comment on "Improved mutual information measure for clustering, classification, and community detection"	A recent article proposed reduced mutual information for evaluation of clustering, classification and community detection. The motivation is that the standard normalized mutual information (NMI) may give counter-intuitive answers under certain conditions and particularly when the number of clusters differs between the ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	177,164
2105.13074	Path-based knowledge reasoning with textual semantic information for medical knowledge graph completion	Background Knowledge graphs (KGs), especially medical knowledge graphs, are often significantly incomplete, so it necessitating a demand for medical knowledge graph completion (MedKGC). MedKGC can find new facts based on the exited knowledge in the KGs. The path-based knowledge reasoning algorithm is one of the most im...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	237,199
2007.08856	EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection	In this paper, we aim at addressing two critical issues in the 3D detection task, including the exploitation of multiple sensors~(namely LiDAR point cloud and camera image), as well as the inconsistency between the localization and classification confidence. To this end, we propose a novel fusion module to enhance the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	187,771
2303.09270	SpectralCLIP: Preventing Artifacts in Text-Guided Style Transfer from a Spectral Perspective	Owing to the power of vision-language foundation models, e.g., CLIP, the area of image synthesis has seen recent important advances. Particularly, for style transfer, CLIP enables transferring more general and abstract styles without collecting the style images in advance, as the style can be efficiently described with...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,977
1909.00109	Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension	Reading comprehension models have been successfully applied to extractive text answers, but it is unclear how best to generalize these models to abstractive numerical answers. We enable a BERT-based reading comprehension model to perform lightweight numerical reasoning. We augment the model with a predefined set of exe...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	143,521
2406.09418	VideoGPT+: Integrating Image and Video Encoders for Enhanced Video Understanding	Building on the advances of language models, Large Multimodal Models (LMMs) have contributed significant improvements in video understanding. While the current video LMMs utilize advanced Large Language Models (LLMs), they rely on either image or video encoders to process visual inputs, each of which has its own limita...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	463,937
1302.3565	Decision-Analytic Approaches to Operational Decision Making: Application and Observation	Decision analysis (DA) and the rich set of tools developed by researchers in decision making under uncertainty show great potential to penetrate the technological content of the products and services delivered by firms in a variety of industries as well as the business processes used to deliver those products and servi...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	22,031
2011.03168	Neural Stochastic Contraction Metrics for Learning-based Control and Estimation	We present Neural Stochastic Contraction Metrics (NSCM), a new design framework for provably-stable robust control and estimation for a class of stochastic nonlinear systems. It uses a spectrally-normalized deep neural network to construct a contraction metric, sampled via simplified convex optimization in the stochast...	false	false	false	false	true	false	true	true	false	false	true	false	false	false	false	false	false	false	205,157
2410.07707	MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting	Dynamic scene reconstruction is a long-term challenge in the field of 3D vision. Recently, the emergence of 3D Gaussian Splatting has provided new insights into this problem. Although subsequent efforts rapidly extend static 3D Gaussian to dynamic scenes, they often lack explicit constraints on object motion, leading t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	496,762
2407.20729	Adapting Safe-for-Work Classifier for Malaysian Language Text: Enhancing Alignment in LLM-Ops Framework	As large language models (LLMs) become increasingly integrated into operational workflows (LLM-Ops), there is a pressing need for effective guardrails to ensure safe and aligned interactions, including the ability to detect potentially unsafe or inappropriate content across languages. However, existing safe-for-work cl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	477,266
2001.00665	Decentralized Langevin Dynamics	Langevin MCMC gradient optimization is a class of increasingly popular methods for estimating a posterior distribution. This paper addresses the algorithm as applied in a decentralized setting, wherein data is distributed across a network of agents which act to cooperatively solve the problem using peer-to-peer gossip ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	159,292
2102.02414	Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization	Many weakly supervised classification methods employ a noise transition matrix to capture the class-conditional label corruption. To estimate the transition matrix from noisy data, existing methods often need to estimate the noisy class-posterior, which could be unreliable due to the overconfidence of neural networks. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	218,401
1105.0275	Robustness of Complex Networks against Attacks Guided by Damage	Extensive researches have been dedicated to investigating the performance of real networks and synthetic networks against random failures or intentional attack guided by degree (degree attack). Degree is one of straightforward measures to characterize the vitality of a vertex in maintaining the integrity of the network...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	10,207
1504.01920	Evaluating Two-Stream CNN for Video Classification	Videos contain very rich semantic information. Traditional hand-crafted features are known to be inadequate in analyzing complex video semantics. Inspired by the huge success of the deep learning methods in analyzing image, audio and text data, significant efforts are recently being devoted to the design of deep nets f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	41,869
2108.02701	Lyapunov Robust Constrained-MDPs: Soft-Constrained Robustly Stable Policy Optimization under Model Uncertainty	Safety and robustness are two desired properties for any reinforcement learning algorithm. CMDPs can handle additional safety constraints and RMDPs can perform well under model uncertainties. In this paper, we propose to unite these two frameworks resulting in robust constrained MDPs (RCMDPs). The motivation is to deve...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	249,415
2309.14395	Implicit Sensing in Traffic Optimization: Advanced Deep Reinforcement Learning Techniques	A sudden roadblock on highways due to many reasons such as road maintenance, accidents, and car repair is a common situation we encounter almost daily. Autonomous Vehicles (AVs) equipped with sensors that can acquire vehicle dynamics such as speed, acceleration, and location can make intelligent decisions to change lan...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	394,597
2305.03632	Improving LaCAM for Scalable Eventually Optimal Multi-Agent Pathfinding	This study extends the recently-developed LaCAM algorithm for multi-agent pathfinding (MAPF). LaCAM is a sub-optimal search-based algorithm that uses lazy successor generation to dramatically reduce the planning effort. We present two enhancements. First, we propose its anytime version, called LaCAM*, which eventually ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	362,462
2502.08108	Generative AI and Empirical Software Engineering: A Paradigm Shift	The widespread adoption of generative AI in software engineering marks a paradigm shift, offering new opportunities to design and utilize software engineering tools while influencing both developers and the artifacts they create. Traditional empirical methods in software engineering, including quantitative, qualitative...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	532,893
2207.14635	Haptic Teleoperation of High-dimensional Robotic Systems Using a Feedback MPC Framework	Model Predictive Control (MPC) schemes have proven their efficiency in controlling high degree-of-freedom (DoF) complex robotic systems. However, they come at a high computational cost and an update rate of about tens of hertz. This relatively slow update rate hinders the possibility of stable haptic teleoperation of s...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	310,655
2110.10295	Expressivity of Neural Networks via Chaotic Itineraries beyond Sharkovsky's Theorem	Given a target function $f$, how large must a neural network be in order to approximate $f$? Recent works examine this basic question on neural network \textit{expressivity} from the lens of dynamical systems and provide novel ``depth-vs-width'' tradeoffs for a large family of functions $f$. They suggest that such trad...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,093
1604.01367	Isogeometric nonlinear bending and buckling analysis of variable-thickness composite plate structures	This paper investigates nonlinear bending and buckling behaviours of composite plates characterized by a thickness variation. Layer interfaces are described as functions of inplane coordinates. Top and bottom surfaces of the plate are symmetric about the midplane and the plate could be considered as a flat surface in a...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	54,189
1301.4783	From 3D Point Clouds To Semantic Objects An Ontology-Based Detection Approach	This paper presents a knowledge-based detection of objects approach using the OWL ontology language, the Semantic Web Rule Language, and 3D processing built-ins aiming at combining geometrical analysis of 3D point clouds and specialist's knowledge. This combination allows the detection and the annotation of objects con...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	21,281
2301.01327	Operator theory, kernels, and Feedforward Neural Networks	In this paper we show how specific families of positive definite kernels serve as powerful tools in analyses of iteration algorithms for multiple layer feedforward Neural Network models. Our focus is on particular kernels that adapt well to learning algorithms for data-sets/features which display intrinsic self-similar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	339,208
2212.12720	Boosting Out-of-Distribution Detection with Multiple Pre-trained Models	Out-of-Distribution (OOD) detection, i.e., identifying whether an input is sampled from a novel distribution other than the training distribution, is a critical task for safely deploying machine learning systems in the open world. Recently, post hoc detection utilizing pre-trained models has shown promising performance...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	338,113
2304.03669	DATE: Domain Adaptive Product Seeker for E-commerce	Product Retrieval (PR) and Grounding (PG), aiming to seek image and object-level products respectively according to a textual query, have attracted great interest recently for better shopping experience. Owing to the lack of relevant datasets, we collect two large-scale benchmark datasets from Taobao Mall and Live doma...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,898
1107.4222	Interference minimization in physical model of wireless networks	Interference minimization problem in wireless sensor and ad-hoc networks is considered. That is to assign a transmission power to each node of a network such that the network is connected and at the same time the maximum of accumulated signal straight on network nodes is minimum. Previous works on interference minimiza...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	11,390
2403.01355	a-DCF: an architecture agnostic metric with application to spoofing-robust speaker verification	Spoofing detection is today a mainstream research topic. Standard metrics can be applied to evaluate the performance of isolated spoofing detection solutions and others have been proposed to support their evaluation when they are combined with speaker detection. These either have well-known deficiencies or restrict the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	434,376
2310.11082	Multi-omics Sampling-based Graph Transformer for Synthetic Lethality Prediction	Synthetic lethality (SL) prediction is used to identify if the co-mutation of two genes results in cell death. The prevalent strategy is to abstract SL prediction as an edge classification task on gene nodes within SL data and achieve it through graph neural networks (GNNs). However, GNNs suffer from limitations in the...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	400,511
2502.06925	Occam's model: Selecting simpler representations for better transferability estimation	Fine-tuning models that have been pre-trained on large datasets has become a cornerstone of modern machine learning workflows. With the widespread availability of online model repositories, such as Hugging Face, it is now easier than ever to fine-tune pre-trained models for specific tasks. This raises a critical questi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	532,356
2301.06304	LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset	We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzen (China). The competition required participants to automatically assess the number of lymphocytes, in particular T-cells, in histopathological images of colon, breast, and prostate cancer sta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	340,615
1505.00444	Some Theoretical Properties of a Network of Discretely Firing Neurons	The problem of optimising a network of discretely firing neurons is addressed. An objective function is introduced which measures the average number of bits that are needed for the network to encode its state. When this is minimised, it is shown that this leads to a number of results, such as topographic mappings, piec...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	42,727
2101.11298	How to Evaluate a Summarizer: Study Design and Statistical Analysis for Manual Linguistic Quality Evaluation	Manual evaluation is essential to judge progress on automatic text summarization. However, we conduct a survey on recent summarization system papers that reveals little agreement on how to perform such evaluation studies. We conduct two evaluation experiments on two aspects of summaries' linguistic quality (coherence a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	217,228
1902.00198	Geometric interpretation of the general POE model for a serial-link robot via conversion into D-H parameterization	While Product of Exponentials (POE) formula has been gaining increasing popularity in modeling the kinematics of a serial-link robot, the Denavit-Hartenberg (D-H) notation is still the most widely used due to its intuitive and concise geometric interpretation of the robot. This paper has developed an analytical solutio...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	120,356
2310.17074	Benign Oscillation of Stochastic Gradient Descent with Large Learning Rates	In this work, we theoretically investigate the generalization properties of neural networks (NN) trained by stochastic gradient descent (SGD) algorithm with large learning rates. Under such a training regime, our finding is that, the oscillation of the NN weights caused by the large learning rate SGD training turns out...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	402,980
2211.02953	Chance-constrained allocation of UFLS candidate feeders under high penetration of distributed generation	Under-Frequency Load Shedding (UFLS) schemes are the last resort to contain a frequency drop in the grid by disconnecting part of the demand. The allocation methods for selecting feeders that would contribute to the UFLS scheme have traditionally relied on the fact that electric demand followed fairly regular patterns,...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	328,768
2412.09775	waveOrder: generalist framework for label-agnostic computational microscopy	Correlative computational microscopy is accelerating the mapping of dynamic biological systems by integrating morphological and molecular measurements across spatial scales, from organelles to entire organisms. Visualization, measurement, and prediction of interactions among the components of biological systems can be ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,637
2402.10980	ChemReasoner: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback	The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic reasoning with quantum-chemistry based feedback from 3D atomistic representations. Our a...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	430,192
1711.06402	Improving Palliative Care with Deep Learning	Improving the quality of end-of-life care for hospitalized patients is a priority for healthcare organizations. Studies have shown that physicians tend to over-estimate prognoses, which in combination with treatment inertia results in a mismatch between patients wishes and actual care at the end of life. We describe a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	84,761
2112.11230	Interpretable Preference-based Reinforcement Learning with Tree-Structured Reward Functions	The potential of reinforcement learning (RL) to deliver aligned and performant agents is partially bottlenecked by the reward engineering problem. One alternative to heuristic trial-and-error is preference-based RL (PbRL), where a reward function is inferred from sparse human feedback. However, prior PbRL methods lack ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	272,647
1707.08482	Confidentiality enforcement by hybrid control of information flows	An information owner, possessing diverse data sources, might want to offer information services based on these sources to cooperation partners and to this end interact with these partners by receiving and sending messages, which the owner on his part generates by program execution. Independently from data representatio...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	77,842
2204.02473	"Does it come in black?" CLIP-like models are zero-shot recommenders	Product discovery is a crucial component for online shopping. However, item-to-item recommendations today do not allow users to explore changes along selected dimensions: given a query item, can a model suggest something similar but in a different color? We consider item recommendations of the comparative nature (e.g. ...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	289,954
2209.10148	Detecting Crop Burning in India using Satellite Data	Crop residue burning is a major source of air pollution in many parts of the world, notably South Asia. Policymakers, practitioners and researchers have invested in both measuring impacts and developing interventions to reduce burning. However, measuring the impacts of burning or the effectiveness of interventions to r...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	318,766
1607.04753	How Much Do Downlink Pilots Improve Cell-Free Massive MIMO?	In this paper, we analyze the benefits of including downlink pilots in a cell-free massive MIMO system. We derive an approximate per-user achievable downlink rate for conjugate beamforming processing, which takes into account both uplink and downlink channel estimation errors, and power control. A performance compariso...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	58,653
1512.01712	Generating News Headlines with Recurrent Neural Networks	We describe an application of an encoder-decoder recurrent neural network with LSTM units and attention to generating headlines from the text of news articles. We find that the model is quite effective at concisely paraphrasing news articles. Furthermore, we study how the neural network decides which input words to pay...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	49,847
2208.08198	Assurance Cases as Foundation Stone for Auditing AI-enabled and Autonomous Systems: Workshop Results and Political Recommendations for Action from the ExamAI Project	The European Machinery Directive and related harmonized standards do consider that software is used to generate safety-relevant behavior of the machinery but do not consider all kinds of software. In particular, software based on machine learning (ML) are not considered for the realization of safety-relevant behavior. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	313,295
2301.04528	The Role of Interactive Visualization in Explaining (Large) NLP Models: from Data to Inference	With a constant increase of learned parameters, modern neural language models become increasingly more powerful. Yet, explaining these complex model's behavior remains a widely unsolved problem. In this paper, we discuss the role interactive visualization can play in explaining NLP models (XNLP). We motivate the use of...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	340,093
2102.00405	BNLP: Natural language processing toolkit for Bengali language	BNLP is an open source language processing toolkit for Bengali language consisting with tokenization, word embedding, POS tagging, NER tagging facilities. BNLP provides pre-trained model with high accuracy to do model based tokenization, embedding, POS tagging, NER tagging task for Bengali language. BNLP pre-trained mo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	217,770
1907.00025	Angular separability of data clusters or network communities in geometrical space and its relevance to hyperbolic embedding	Analysis of 'big data' characterized by high-dimensionality such as word vectors and complex networks requires often their representation in a geometrical space by embedding. Recent developments in machine learning and network geometry have pointed out the hyperbolic space as a useful framework for the representation o...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	136,917
2108.04058	An Interpretable Probabilistic Model for Short-Term Solar Power Forecasting Using Natural Gradient Boosting	PV power forecasting models are predominantly based on machine learning algorithms which do not provide any insight into or explanation about their predictions (black boxes). Therefore, their direct implementation in environments where transparency is required, and the trust associated with their predictions may be que...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	249,877
1912.09902	Dependable Neural Networks for Safety Critical Tasks	Neural Networks are being integrated into safety critical systems, e.g., perception systems for autonomous vehicles, which require trained networks to perform safely in novel scenarios. It is challenging to verify neural networks because their decisions are not explainable, they cannot be exhaustively tested, and finit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	158,175
2208.10442	Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks	A big convergence of language, vision, and multimodal pretraining is emerging. In this work, we introduce a general-purpose multimodal foundation model BEiT-3, which achieves state-of-the-art transfer performance on both vision and vision-language tasks. Specifically, we advance the big convergence from three aspects: ...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	314,063
2409.02347	Understanding the Role of Functional Diversity in Weight-Ensembling with Ingredient Selection and Multidimensional Scaling	Weight-ensembles are formed when the parameters of multiple neural networks are directly averaged into a single model. They have demonstrated generalization capability in-distribution (ID) and out-of-distribution (OOD) which is not completely understood, though they are thought to successfully exploit functional divers...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	485,662
2006.07804	Vietnamese Word Segmentation with SVM: Ambiguity Reduction and Suffix Capture	In this paper, we approach Vietnamese word segmentation as a binary classification by using the Support Vector Machine classifier. We inherit features from prior works such as n-gram of syllables, n-gram of syllable types, and checking conjunction of adjacent syllables in the dictionary. We propose two novel ways to fe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	181,948
2312.17394	Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization	The integration of constrained optimization models as components in deep networks has led to promising advances on many specialized learning tasks. A central challenge in this setting is backpropagation through the solution of an optimization problem, which often lacks a closed form. One typical strategy is algorithm u...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	418,734
1902.06040	A Timer-Augmented Cost Function for Load Balanced DSMC	Due to a hard dependency between time steps, large-scale simulations of gas using the Direct Simulation Monte Carlo (DSMC) method proceed at the pace of the slowest processor. Scalability is therefore achievable only by ensuring that the work done each time step is as evenly apportioned among the processors as possible...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	121,668
2211.07245	Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition	The ROC curve is the major tool for assessing not only the performance but also the fairness properties of a similarity scoring function. In order to draw reliable conclusions based on empirical ROC analysis, accurately evaluating the uncertainty level related to statistical versions of the ROC curves of interest is ab...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	330,170
1807.02290	Differentially Private Online Submodular Optimization	In this paper we develop the first algorithms for online submodular minimization that preserve differential privacy under full information feedback and bandit feedback. A sequence of $T$ submodular functions over a collection of $n$ elements arrive online, and at each timestep the algorithm must choose a subset of $[n]...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	102,239
2311.09774	HuatuoGPT-II, One-stage Training for Medical Adaption of LLMs	Adapting a language model into a specific domain, a.k.a `domain adaption', is a common practice when specialized knowledge, e.g. medicine, is not encapsulated in a general language model like Llama2. The challenge lies in the heterogeneity of data across the two training stages, as it varies in languages, genres, or fo...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	408,288
2008.11833	Deep learning-based computer vision to recognize and classify suturing gestures in robot-assisted surgery	Our previous work classified a taxonomy of suturing gestures during a vesicourethral anastomosis of robotic radical prostatectomy in association with tissue tears and patient outcomes. Herein, we train deep-learning based computer vision (CV) to automate the identification and classification of suturing gestures for ne...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	193,392
2111.01351	Major Depressive Disorder Recognition and Cognitive Analysis Based on Multi-layer Brain Functional Connectivity Networks	On the increase of major depressive disorders (MDD), many researchers paid attention to their recognition and treatment. Existing MDD recognition algorithms always use a single time-frequency domain method method, but the single time-frequency domain method is too simple and is not conducive to simulating the complex l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	264,528
1903.11158	Weighted Multisource Tradaboost	In this paper we propose an improved method for transfer learning that takes into account the balance between target and source data. This method builds on the state-of-the-art Multisource Tradaboost, but weighs the importance of each datapoint taking into account the amount of target and source data available. A compa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	125,438
1910.10775	Functional Tensors for Probabilistic Programming	It is a significant challenge to design probabilistic programming systems that can accommodate a wide variety of inference strategies within a unified framework. Noting that the versatility of modern automatic differentiation frameworks is based in large part on the unifying concept of tensors, we describe a software a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	150,575
2006.10923	Hyperparameter Analysis for Image Captioning	In this paper, we perform a thorough sensitivity analysis on state-of-the-art image captioning approaches using two different architectures: CNN+LSTM and CNN+Transformer. Experiments were carried out using the Flickr8k dataset. The biggest takeaway from the experiments is that fine-tuning the CNN encoder outperforms th...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	183,043
2401.07646	Multifractal-spectral features enhance classification of anomalous diffusion	Anomalous diffusion processes pose a unique challenge in classification and characterization. Previously (Mangalam et al., 2023, Physical Review Research 5, 023144), we established a framework for understanding anomalous diffusion using multifractal formalism. The present study delves into the potential of multifractal...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	421,614
2502.02696	How Inclusively do LMs Perceive Social and Moral Norms?	This paper discusses and contains offensive content. Language models (LMs) are used in decision-making systems and as interactive assistants. However, how well do these models making judgements align with the diversity of human values, particularly regarding social and moral norms? In this work, we investigate how incl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	530,430
2203.04050	BEVSegFormer: Bird's Eye View Semantic Segmentation From Arbitrary Camera Rigs	Semantic segmentation in bird's eye view (BEV) is an important task for autonomous driving. Though this task has attracted a large amount of research efforts, it is still challenging to flexibly cope with arbitrary (single or multiple) camera sensors equipped on the autonomous vehicle. In this paper, we present BEVSegF...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	284,334
2312.05925	Language-Conditioned Semantic Search-Based Policy for Robotic Manipulation Tasks	Reinforcement learning and Imitation Learning approaches utilize policy learning strategies that are difficult to generalize well with just a few examples of a task. In this work, we propose a language-conditioned semantic search-based method to produce an online search-based policy from the available demonstration dat...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	414,299
2409.07412	Manifold Learning via Foliations and Knowledge Transfer	Understanding how real data is distributed in high dimensional spaces is the key to many tasks in machine learning. We want to provide a natural geometric structure on the space of data employing a deep ReLU neural network trained as a classifier. Through the data information matrix (DIM), a variation of the Fisher inf...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	487,505
1811.06868	Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations	We consider the problem of fine-grained classification on an edge camera device that has limited power. The edge device must sparingly interact with the cloud to minimize communication bits to conserve power, and the cloud upon receiving the edge inputs returns a classification label. To deal with fine-grained classifi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	113,613
2401.13085	IndiText Boost: Text Augmentation for Low Resource India Languages	Text Augmentation is an important task for low-resource languages. It helps deal with the problem of data scarcity. A data augmentation strategy is used to deal with the problem of data scarcity. Through the years, much work has been done on data augmentation for the English language. In contrast, very less work has be...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	423,602
1909.01968	ACES -- Automatic Configuration of Energy Harvesting Sensors with Reinforcement Learning	Internet of Things forms the backbone of modern building applications. Wireless sensors are being increasingly adopted for their flexibility and reduced cost of deployment. However, most wireless sensors are powered by batteries today and large deployments are inhibited by manual battery replacement. Energy harvesting ...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	144,063
2008.11290	Extractive Summarizer for Scholarly Articles	We introduce an extractive method that will summarize long scientific papers. Our model uses presentation slides provided by the authors of the papers as the gold summary standard to label the sentences. The sentences are ranked based on their novelty and their importance as estimated by deep neural networks. Our windo...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	193,226
2006.08372	Fast algebraic immunity of Boolean functions and LCD codes	Nowadays, the resistance against algebraic attacks and fast algebraic attacks are considered as an important cryptographic property for Boolean functions used in stream ciphers. Both attacks are very powerful analysis concepts and can be applied to symmetric cryptographic algorithms used in stream ciphers. The notion o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	182,170
2203.00502	Sensor technologies in cancer research for new directions in diagnosis and treatment: and exploratory analysis	The goal of this study is an exploratory analysis concerning main sensor technologies applied in cancer research to detect new directions in diagnosis and treatments. The study focused on types of cancer having a high incidence and mortality worldwide: breast, lung, colorectal and prostate. Data of the Web of Science (...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	283,022

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