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
2501.00608	Optimizing Speech-Input Length for Speaker-Independent Depression Classification	Machine learning models for speech-based depression classification offer promise for health care applications. Despite growing work on depression classification, little is understood about how the length of speech-input impacts model performance. We analyze results for speaker-independent depression classification usin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	521,727
2407.16308	SAFNet: Selective Alignment Fusion Network for Efficient HDR Imaging	Multi-exposure High Dynamic Range (HDR) imaging is a challenging task when facing truncated texture and complex motion. Existing deep learning-based methods have achieved great success by either following the alignment and fusion pipeline or utilizing attention mechanism. However, the large computation cost and inferen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	475,551
2404.09916	Comprehensive Library of Variational LSE Solvers	Linear systems of equations can be found in various mathematical domains, as well as in the field of machine learning. By employing noisy intermediate-scale quantum devices, variational solvers promise to accelerate finding solutions for large systems. Although there is a wealth of theoretical research on these algorit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	446,880
1807.01164	A Decoupled Data Based Approach to Stochastic Optimal Control Problems	This paper studies the stochastic optimal control problem for systems with unknown dynamics. A novel decoupled data based control (D2C) approach is proposed, which solves the problem in a decoupled "open loop-closed loop" fashion that is shown to be near-optimal. First, an open-loop deterministic trajectory optimizatio...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	101,999
1701.01654	Application of Fuzzy Logic in Design of Smart Washing Machine	Washing machine is of great domestic necessity as it frees us from the burden of washing our clothes and saves ample of our time. This paper will cover the aspect of designing and developing of Fuzzy Logic based, Smart Washing Machine. The regular washing machine (timer based) makes use of multi-turned timer based star...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	66,433
2403.14171	MMIDR: Teaching Large Language Model to Interpret Multimodal Misinformation via Knowledge Distillation	Automatic detection of multimodal misinformation has gained a widespread attention recently. However, the potential of powerful Large Language Models (LLMs) for multimodal misinformation detection remains underexplored. Besides, how to teach LLMs to interpret multimodal misinformation in cost-effective and accessible w...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	439,948
1707.05562	One-Shot Learning in Discriminative Neural Networks	We consider the task of one-shot learning of visual categories. In this paper we explore a Bayesian procedure for updating a pretrained convnet to classify a novel image category for which data is limited. We decompose this convnet into a fixed feature extractor and softmax classifier. We assume that the target weights...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	77,256
1411.0659	Approximate Counting in SMT and Value Estimation for Probabilistic Programs	#SMT, or model counting for logical theories, is a well-known hard problem that generalizes such tasks as counting the number of satisfying assignments to a Boolean formula and computing the volume of a polytope. In the realm of satisfiability modulo theories (SMT) there is a growing need for model counting solvers, co...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	37,271
2410.09019	MedMobile: A mobile-sized language model with expert-level clinical capabilities	Language models (LMs) have demonstrated expert-level reasoning and recall abilities in medicine. However, computational costs and privacy concerns are mounting barriers to wide-scale implementation. We introduce a parsimonious adaptation of phi-3-mini, MedMobile, a 3.8 billion parameter LM capable of running on a mobil...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	497,393
1307.3712	Reconstruction of gene regulatory network of colon cancer using information theoretic approach	Reconstruction of gene regulatory networks or 'reverse-engineering' is a process of identifying gene interaction networks from experimental microarray gene expression profile through computation techniques. In this paper, we tried to reconstruct cancer-specific gene regulatory network using information theoretic approa...	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	25,825
2208.04664	Application of federated learning in manufacturing	A vast amount of data is created every minute, both in the private sector and industry. Whereas it is often easy to get hold of data in the private entertainment sector, in the industrial production environment it is much more difficult due to laws, preservation of intellectual property, and other factors. However, mos...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	312,188
2407.02683	Generalized Event Cameras	Event cameras capture the world at high time resolution and with minimal bandwidth requirements. However, event streams, which only encode changes in brightness, do not contain sufficient scene information to support a wide variety of downstream tasks. In this work, we design generalized event cameras that inherently p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	469,837
2402.04507	A Review on Digital Pixel Sensors	Digital pixel sensor (DPS) has evolved as a pivotal component in modern imaging systems and has the potential to revolutionize various fields such as medical imaging, astronomy, surveillance, IoT devices, etc. Compared to analog pixel sensors, the DPS offers high speed and good image quality. However, the introduced in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	427,479
2009.11977	An original framework for Wheat Head Detection using Deep, Semi-supervised and Ensemble Learning within Global Wheat Head Detection (GWHD) Dataset	In this paper, we propose an original object detection methodology applied to Global Wheat Head Detection (GWHD) Dataset. We have been through two major architectures of object detection which are FasterRCNN and EfficientDet, in order to design a novel and robust wheat head detection model. We emphasize on optimizing t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	197,298
2209.06906	Nonlinear dynamics of asymmetric bistable energy harvesters	The paper investigates asymmetries effects over a nonlinear vibration energy harvester dynamics. The asymmetric system performance is compared with symmetric ones. Different asymmetry levels on restoring force and gravity action are investigated from a system-sloping angle variation. Bifurcation diagrams and basins of ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	317,545
2407.14655	LORTSAR: Low-Rank Transformer for Skeleton-based Action Recognition	The complexity of state-of-the-art Transformer-based models for skeleton-based action recognition poses significant challenges in terms of computational efficiency and resource utilization. In this paper, we explore the application of Singular Value Decomposition (SVD) to effectively reduce the model sizes of these pre...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	474,857
2205.15712	Multilingual Transformers for Product Matching -- Experiments and a New Benchmark in Polish	Product matching corresponds to the task of matching identical products across different data sources. It typically employs available product features which, apart from being multimodal, i.e., comprised of various data types, might be non-homogeneous and incomplete. The paper shows that pre-trained, multilingual Transf...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	299,840
2307.04319	New Variants of Frank-Wolfe Algorithm for Video Co-localization Problem	The co-localization problem is a model that simultaneously localizes objects of the same class within a series of images or videos. In \cite{joulin2014efficient}, authors present new variants of the Frank-Wolfe algorithm (aka conditional gradient) that increase the efficiency in solving the image and video co-localizat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	378,355
2208.04381	Dual-Blind Deconvolution for Overlaid Radar-Communications Systems	The increasingly crowded spectrum has spurred the design of joint radar-communications systems that share hardware resources and efficiently use the radio frequency spectrum. We study a general spectral coexistence scenario, wherein the channels and transmit signals of both radar and communications systems are unknown ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	312,094
1711.07693	Regret Analysis for Continuous Dueling Bandit	The dueling bandit is a learning framework wherein the feedback information in the learning process is restricted to a noisy comparison between a pair of actions. In this research, we address a dueling bandit problem based on a cost function over a continuous space. We propose a stochastic mirror descent algorithm and ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	85,053
1902.07249	Discovery of Natural Language Concepts in Individual Units of CNNs	Although deep convolutional networks have achieved improved performance in many natural language tasks, they have been treated as black boxes because they are difficult to interpret. Especially, little is known about how they represent language in their intermediate layers. In an attempt to understand the representatio...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	121,937
2310.06109	QR-Tag: Angular Measurement and Tracking with a QR-Design Marker	Directional information measurement has many applications in domains such as robotics, virtual and augmented reality, and industrial computer vision. Conventional methods either require pre-calibration or necessitate controlled environments. The state-of-the-art MoireTag approach exploits the Moire effect and QR-design...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	398,422
2407.18462	MistralBSM: Leveraging Mistral-7B for Vehicular Networks Misbehavior Detection	Vehicular networks are exposed to various threats resulting from malicious attacks. These threats compromise the security and reliability of communications among road users, thereby jeopardizing road and traffic safety. One of the main vectors of these attacks within vehicular networks is misbehaving vehicles. To addre...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	476,377
2202.05631	Vehicle and License Plate Recognition with Novel Dataset for Toll Collection	We propose an automatic framework for toll collection, consisting of three steps: vehicle type recognition, license plate localization, and reading. However, each of the three steps becomes non-trivial due to image variations caused by several factors. The traditional vehicle decorations on the front cause variations a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	279,934
2406.05863	Source -Free Domain Adaptation for Speaker Verification in Data-Scarce Languages and Noisy Channels	Domain adaptation is often hampered by exceedingly small target datasets and inaccessible source data. These conditions are prevalent in speech verification, where privacy policies and/or languages with scarce speech resources limit the availability of sufficient data. This paper explored techniques of sourcefree domai...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	462,326
2501.09617	WMamba: Wavelet-based Mamba for Face Forgery Detection	With the rapid advancement of deepfake generation technologies, the demand for robust and accurate face forgery detection algorithms has become increasingly critical. Recent studies have demonstrated that wavelet analysis can uncover subtle forgery artifacts that remain imperceptible in the spatial domain. Wavelets eff...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	525,204
1206.6323	Local implementations of non-local quantum gates in linear entangled channel	In this paper, we demonstrate n-party controlled unitary gate implementations locally on arbitrary remote state through linear entangled channel where control parties share entanglement with the adjacent control parties and only one of them shares entanglement with the target party. In such a network, we describe the p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,911
1607.08400	Randomised Algorithm for Feature Selection and Classification	We here introduce a novel classification approach adopted from the nonlinear model identification framework, which jointly addresses the feature selection and classifier design tasks. The classifier is constructed as a polynomial expansion of the original attributes and a model structure selection process is applied to...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	59,155
1903.01021	A Strongly Asymptotically Optimal Agent in General Environments	Reinforcement Learning agents are expected to eventually perform well. Typically, this takes the form of a guarantee about the asymptotic behavior of an algorithm given some assumptions about the environment. We present an algorithm for a policy whose value approaches the optimal value with probability 1 in all computa...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	123,168
2002.00476	Sound Event Detection with Depthwise Separable and Dilated Convolutions	State-of-the-art sound event detection (SED) methods usually employ a series of convolutional neural networks (CNNs) to extract useful features from the input audio signal, and then recurrent neural networks (RNNs) to model longer temporal context in the extracted features. The number of the channels of the CNNs and si...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	162,357
2112.13545	ViR:the Vision Reservoir	The most recent year has witnessed the success of applying the Vision Transformer (ViT) for image classification. However, there are still evidences indicating that ViT often suffers following two aspects, i) the high computation and the memory burden from applying the multiple Transformer layers for pre-training on a ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	273,280
2308.05444	How-to Augmented Lagrangian on Factor Graphs	Factor graphs are a very powerful graphical representation, used to model many problems in robotics. They are widely spread in the areas of Simultaneous Localization and Mapping (SLAM), computer vision, and localization. In this paper we describe an approach to fill the gap with other areas, such as optimal control, by...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	384,793
2410.09821	DAS3D: Dual-modality Anomaly Synthesis for 3D Anomaly Detection	Synthesizing anomaly samples has proven to be an effective strategy for self-supervised 2D industrial anomaly detection. However, this approach has been rarely explored in multi-modality anomaly detection, particularly involving 3D and RGB images. In this paper, we propose a novel dual-modality augmentation method for ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	497,784
2307.14242	Defending Adversarial Patches via Joint Region Localizing and Inpainting	Deep neural networks are successfully used in various applications, but show their vulnerability to adversarial examples. With the development of adversarial patches, the feasibility of attacks in physical scenes increases, and the defenses against patch attacks are urgently needed. However, defending such adversarial ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	381,856
2302.11074	Preventing Catastrophic Forgetting in Continual Learning of New Natural Language Tasks	Multi-Task Learning (MTL) is widely-accepted in Natural Language Processing as a standard technique for learning multiple related tasks in one model. Training an MTL model requires having the training data for all tasks available at the same time. As systems usually evolve over time, (e.g., to support new functionaliti...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	347,076
1109.6880	Explanation-Based Auditing	To comply with emerging privacy laws and regulations, it has become common for applications like electronic health records systems (EHRs) to collect access logs, which record each time a user (e.g., a hospital employee) accesses a piece of sensitive data (e.g., a patient record). Using the access log, it is easy to ans...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	12,419
2210.00717	Evolution of flexible industrial assembly	Assembly is a key industrial process to achieve finished goods. Driven by market demographics and technological advancements, industrial assembly has evolved through several phases i.e. craftmanship, bench assembly, assembly lines and flexible assembly cells. Due to the complexity and variety of assembly tasks, besides...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	320,974
2103.04558	CRLF: Automatic Calibration and Refinement based on Line Feature for LiDAR and Camera in Road Scenes	For autonomous vehicles, an accurate calibration for LiDAR and camera is a prerequisite for multi-sensor perception systems. However, existing calibration techniques require either a complicated setting with various calibration targets, or an initial calibration provided beforehand, which greatly impedes their applicab...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	223,687
1911.11929	CSPNet: A New Backbone that can Enhance Learning Capability of CNN	Neural networks have enabled state-of-the-art approaches to achieve incredible results on computer vision tasks such as object detection. However, such success greatly relies on costly computation resources, which hinders people with cheap devices from appreciating the advanced technology. In this paper, we propose Cro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	155,260
2202.03677	A Novel Image Descriptor with Aggregated Semantic Skeleton Representation for Long-term Visual Place Recognition	In a Simultaneous Localization and Mapping (SLAM) system, a loop-closure can eliminate accumulated errors, which is accomplished by Visual Place Recognition (VPR), a task that retrieves the current scene from a set of pre-stored sequential images through matching specific scene-descriptors. In urban scenes, the appeara...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	279,302
2206.03669	Toward Certified Robustness Against Real-World Distribution Shifts	We consider the problem of certifying the robustness of deep neural networks against real-world distribution shifts. To do so, we bridge the gap between hand-crafted specifications and realistic deployment settings by proposing a novel neural-symbolic verification framework, in which we train a generative model to lear...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	301,364
2302.07344	Semi-Supervised Visual Tracking of Marine Animals using Autonomous Underwater Vehicles	In-situ visual observations of marine organisms is crucial to developing behavioural understandings and their relations to their surrounding ecosystem. Typically, these observations are collected via divers, tags, and remotely-operated or human-piloted vehicles. Recently, however, autonomous underwater vehicles equippe...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	345,695
1904.03868	Noise-Aware Unsupervised Deep Lidar-Stereo Fusion	In this paper, we present LidarStereoNet, the first unsupervised Lidar-stereo fusion network, which can be trained in an end-to-end manner without the need of ground truth depth maps. By introducing a novel "Feedback Loop'' to connect the network input with output, LidarStereoNet could tackle both noisy Lidar points an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,865
2310.09969	Socially Acceptable Bipedal Navigation: A Signal-Temporal-Logic- Driven Approach for Safe Locomotion	Social navigation for bipedal robots remains relatively unexplored due to the highly complex, nonlinear dynamics of bipedal locomotion. This study presents a preliminary exploration of social navigation for bipedal robots in a human crowded environment. We propose a social path planner that ensures the locomotion safet...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	400,022
1805.01984	Various Approaches to Aspect-based Sentiment Analysis	The problem of aspect-based sentiment analysis deals with classifying sentiments (negative, neutral, positive) for a given aspect in a sentence. A traditional sentiment classification task involves treating the entire sentence as a text document and classifying sentiments based on all the words. Let us assume, we have ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	96,748
2209.13586	Learning-Based Dimensionality Reduction for Computing Compact and Effective Local Feature Descriptors	A distinctive representation of image patches in form of features is a key component of many computer vision and robotics tasks, such as image matching, image retrieval, and visual localization. State-of-the-art descriptors, from hand-crafted descriptors such as SIFT to learned ones such as HardNet, are usually high di...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	319,957
2402.07467	You can monitor your hydration level using your smartphone camera	This work proposes for the first time to utilize the regular smartphone -- a popular assistive gadget -- to design a novel, non-invasive method for self-monitoring of one's hydration level on a scale of 1 to 4. The proposed method involves recording a small video of a fingertip using the smartphone camera. Subsequently...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	428,734
2404.19071	Blind Spots and Biases: Exploring the Role of Annotator Cognitive Biases in NLP	With the rapid proliferation of artificial intelligence, there is growing concern over its potential to exacerbate existing biases and societal disparities and introduce novel ones. This issue has prompted widespread attention from academia, policymakers, industry, and civil society. While evidence suggests that integr...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	450,491
2203.08500	HeterMPC: A Heterogeneous Graph Neural Network for Response Generation in Multi-Party Conversations	Recently, various response generation models for two-party conversations have achieved impressive improvements, but less effort has been paid to multi-party conversations (MPCs) which are more practical and complicated. Compared with a two-party conversation where a dialogue context is a sequence of utterances, buildin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	285,815
1901.00243	Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams	In many real-world learning scenarios, features are only acquirable at a cost constrained under a budget. In this paper, we propose a novel approach for cost-sensitive feature acquisition at the prediction-time. The suggested method acquires features incrementally based on a context-aware feature-value function. We for...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	117,729
2409.01219	A Review of Image Retrieval Techniques: Data Augmentation and Adversarial Learning Approaches	Image retrieval is a crucial research topic in computer vision, with broad application prospects ranging from online product searches to security surveillance systems. In recent years, the accuracy and efficiency of image retrieval have significantly improved due to advancements in deep learning. However, existing meth...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	485,260
2303.12376	Graph Data Models and Relational Database Technology	Recent work on database application development platforms has sought to include a declarative formulation of a conceptual data model in the application code, using annotations or attributes. Some recent work has used metadata to include the details of such formulations in the physical database, and this approach brings...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	353,247
1301.2270	Multivariate Information Bottleneck	The Information bottleneck method is an unsupervised non-parametric data organization technique. Given a joint distribution P(A,B), this method constructs a new variable T that extracts partitions, or clusters, over the values of A that are informative about B. The information bottleneck has already been applied to doc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	20,946
1602.08361	Certified Universal Gathering in $R^2$ for Oblivious Mobile Robots	We present a unified formal framework for expressing mobile robots models, protocols, and proofs, and devise a protocol design/proof methodology dedicated to mobile robots that takes advantage of this formal framework. As a case study, we present the first formally certified protocol for oblivious mobile robots evolvin...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	52,635
2111.06685	DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents	Scalability and accuracy are well recognized challenges in deep extreme multi-label learning where the objective is to train architectures for automatically annotating a data point with the most relevant subset of labels from an extremely large label set. This paper develops the DeepXML framework that addresses these c...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	266,145
1603.08637	Learning a Predictable and Generative Vector Representation for Objects	What is a good vector representation of an object? We believe that it should be generative in 3D, in the sense that it can produce new 3D objects; as well as be predictable from 2D, in the sense that it can be perceived from 2D images. We propose a novel architecture, called the TL-embedding network, to learn an embedd...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	53,811
2501.16671	Data-Free Model-Related Attacks: Unleashing the Potential of Generative AI	Generative AI technology has become increasingly integrated into our daily lives, offering powerful capabilities to enhance productivity. However, these same capabilities can be exploited by adversaries for malicious purposes. While existing research on adversarial applications of generative AI predominantly focuses on...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	528,058
2206.03043	COVIDx CT-3: A Large-scale, Multinational, Open-Source Benchmark Dataset for Computer-aided COVID-19 Screening from Chest CT Images	Computed tomography (CT) has been widely explored as a COVID-19 screening and assessment tool to complement RT-PCR testing. To assist radiologists with CT-based COVID-19 screening, a number of computer-aided systems have been proposed. However, many proposed systems are built using CT data which is limited in both quan...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	301,129
1903.01855	TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning	TensorFlow Eager is a multi-stage, Python-embedded domain-specific language for hardware-accelerated machine learning, suitable for both interactive research and production. TensorFlow, which TensorFlow Eager extends, requires users to represent computations as dataflow graphs; this permits compiler optimizations and s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	123,351
2405.14094	Attending to Topological Spaces: The Cellular Transformer	Topological Deep Learning seeks to enhance the predictive performance of neural network models by harnessing topological structures in input data. Topological neural networks operate on spaces such as cell complexes and hypergraphs, that can be seen as generalizations of graphs. In this work, we introduce the Cellular ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	456,243
2312.11146	OsmLocator: locating overlapping scatter marks with a non-training generative perspective	Automated mark localization in scatter images, greatly helpful for discovering knowledge and understanding enormous document images and reasoning in visual question answering AI systems, is a highly challenging problem because of the ubiquity of overlapping marks. Locating overlapping marks faces many difficulties such...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	416,460
2404.01059	STAR-RIS Aided Secure MIMO Communication Systems	This paper investigates simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) aided physical layer security (PLS) in multiple-input multiple-output (MIMO) systems, where the base station (BS) transmits secrecy information with the aid of STAR-RIS against multiple eavesdroppers equipped ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	443,232
2107.00783	Reinforcement Learning for Feedback-Enabled Cyber Resilience	Digitization and remote connectivity have enlarged the attack surface and made cyber systems more vulnerable. As attackers become increasingly sophisticated and resourceful, mere reliance on traditional cyber protection, such as intrusion detection, firewalls, and encryption, is insufficient to secure the cyber systems...	false	false	false	false	false	false	true	false	false	false	true	false	true	false	false	false	false	false	244,269
2012.09432	On the experimental feasibility of quantum state reconstruction via machine learning	We determine the resource scaling of machine learning-based quantum state reconstruction methods, in terms of inference and training, for systems of up to four qubits when constrained to pure states. Further, we examine system performance in the low-count regime, likely to be encountered in the tomography of high-dimen...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	212,079
2105.04278	A Rate-Distortion Framework for Characterizing Semantic Information	A rate-distortion problem motivated by the consideration of semantic information is formulated and solved. The starting point is to model an information source as a pair consisting of an intrinsic state which is not observable, corresponding to the semantic aspect of the source, and an extrinsic observation which is su...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	234,456
1811.07173	Person Identification and Body Mass Index: A Deep Learning-Based Study on Micro-Dopplers	Obtaining a smart surveillance requires a sensing system that can capture accurate and detailed information for the human walking style. The radar micro-Doppler ($\boldsymbol{\mu}$-D) analysis is proved to be a reliable metric for studying human locomotions. Thus, $\boldsymbol{\mu}$-D signatures can be used to identify...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	113,694
2412.02825	Many-MobileNet: Multi-Model Augmentation for Robust Retinal Disease Classification	In this work, we propose Many-MobileNet, an efficient model fusion strategy for retinal disease classification using lightweight CNN architecture. Our method addresses key challenges such as overfitting and limited dataset variability by training multiple models with distinct data augmentation strategies and different ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,694
1909.05421	Speculative Beam Search for Simultaneous Translation	Beam search is universally used in full-sentence translation but its application to simultaneous translation remains non-trivial, where output words are committed on the fly. In particular, the recently proposed wait-k policy (Ma et al., 2019a) is a simple and effective method that (after an initial wait) commits one o...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	145,093
1908.06760	Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction	Predicting drug-target interactions (DTI) is an essential part of the drug discovery process, which is an expensive process in terms of time and cost. Therefore, reducing DTI cost could lead to reduced healthcare costs for a patient. In addition, a precisely learned molecule representation in a DTI model could contribu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	142,108
2204.07716	FKreg: A MATLAB toolbox for fast Multivariate Kernel Regression	Kernel smooth is the most fundamental technique for data density and regression estimation. However, time-consuming is the biggest obstacle for the application that the direct evaluation of kernel smooth for $N$ samples needs ${O}\left( {{N}^{2}} \right)$ operations. People have developed fast smooth algorithms using t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	291,813
2106.08981	Nonequilibrium thermodynamics of self-supervised learning	Self-supervised learning (SSL) of energy based models has an intuitive relation to equilibrium thermodynamics because the softmax layer, mapping energies to probabilities, is a Gibbs distribution. However, in what way SSL is a thermodynamic process? We show that some SSL paradigms behave as a thermodynamic composite sy...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	241,504
2301.11226	Community Detection in Large Hypergraphs	Hypergraphs, describing networks where interactions take place among any number of units, are a natural tool to model many real-world social and biological systems. In this work we propose a principled framework to model the organization of higher-order data. Our approach recovers community structure with accuracy exce...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	342,059
2305.15159	Collaborative Recommendation Model Based on Multi-modal Multi-view Attention Network: Movie and literature cases	The existing collaborative recommendation models that use multi-modal information emphasize the representation of users' preferences but easily ignore the representation of users' dislikes. Nevertheless, modelling users' dislikes facilitates comprehensively characterizing user profiles. Thus, the representation of user...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	367,482
2412.03297	Composed Image Retrieval for Training-Free Domain Conversion	This work addresses composed image retrieval in the context of domain conversion, where the content of a query image is retrieved in the domain specified by the query text. We show that a strong vision-language model provides sufficient descriptive power without additional training. The query image is mapped to the tex...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,904
2308.12063	Learning the Plasticity: Plasticity-Driven Learning Framework in Spiking Neural Networks	The evolution of the human brain has led to the development of complex synaptic plasticity, enabling dynamic adaptation to a constantly evolving world. This progress inspires our exploration into a new paradigm for Spiking Neural Networks (SNNs): a Plasticity-Driven Learning Framework (PDLF). This paradigm diverges fro...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	387,405
2310.00589	Structural Controllability of Bilinear Systems on $\mathbb{SE(n)}$	Structural controllability challenges arise from imprecise system modeling and system interconnections in large scale systems. In this paper, we study structural control of bilinear systems on the special Euclidean group. We employ graph theoretic methods to analyze the structural controllability problem for driftless ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	396,053
1702.07281	A Probabilistic Framework for Location Inference from Social Media	We study the extent to which we can infer users' geographical locations from social media. Location inference from social media can benefit many applications, such as disaster management, targeted advertising, and news content tailoring. The challenges, however, lie in the limited amount of labeled data and the large s...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	68,754
2407.03217	MHNet: Multi-view High-order Network for Diagnosing Neurodevelopmental Disorders Using Resting-state fMRI	Background: Deep learning models have shown promise in diagnosing neurodevelopmental disorders (NDD) like ASD and ADHD. However, many models either use graph neural networks (GNN) to construct single-level brain functional networks (BFNs) or employ spatial convolution filtering for local information extraction from rs-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,076
1803.01489	Recurrent Predictive State Policy Networks	We introduce Recurrent Predictive State Policy (RPSP) networks, a recurrent architecture that brings insights from predictive state representations to reinforcement learning in partially observable environments. Predictive state policy networks consist of a recursive filter, which keeps track of a belief about the stat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	91,891
2308.01940	TSMD: A Database for Static Color Mesh Quality Assessment Study	Static meshes with texture map are widely used in modern industrial and manufacturing sectors, attracting considerable attention in the mesh compression community due to its huge amount of data. To facilitate the study of static mesh compression algorithm and objective quality metric, we create the Tencent - Static Mes...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	383,426
2312.08987	Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model	Signal peptide (SP) is a short peptide located in the N-terminus of proteins. It is essential to target and transfer transmembrane and secreted proteins to correct positions. Compared with traditional experimental methods to identify signal peptides, computational methods are faster and more efficient, which are more p...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	415,547
0910.1857	Distributed Object Medical Imaging Model	Digital medical informatics and images are commonly used in hospitals today,. Because of the interrelatedness of the radiology department and other departments, especially the intensive care unit and emergency department, the transmission and sharing of medical images has become a critical issue. Our research group has...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	4,695
2102.08244	Differentially Private Quantiles	Quantiles are often used for summarizing and understanding data. If that data is sensitive, it may be necessary to compute quantiles in a way that is differentially private, providing theoretical guarantees that the result does not reveal private information. However, when multiple quantiles are needed, existing differ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	220,386
1908.08659	A Comparison of Action Spaces for Learning Manipulation Tasks	Designing reinforcement learning (RL) problems that can produce delicate and precise manipulation policies requires careful choice of the reward function, state, and action spaces. Much prior work on applying RL to manipulation tasks has defined the action space in terms of direct joint torques or reference positions f...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	142,617
1909.00229	UPI-Net: Semantic Contour Detection in Placental Ultrasound	Semantic contour detection is a challenging problem that is often met in medical imaging, of which placental image analysis is a particular example. In this paper, we investigate utero-placental interface (UPI) detection in 2D placental ultrasound images by formulating it as a semantic contour detection problem. As opp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	143,572
2004.11005	Love, Joy, Anger, Sadness, Fear, and Surprise: SE Needs Special Kinds of AI: A Case Study on Text Mining and SE	Do you like your code? What kind of code makes developers happiest? What makes them angriest? Is it possible to monitor the mood of a large team of coders to determine when and where a codebase needs additional help?	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	173,790
2112.01433	Loss Landscape Dependent Self-Adjusting Learning Rates in Decentralized Stochastic Gradient Descent	Distributed Deep Learning (DDL) is essential for large-scale Deep Learning (DL) training. Synchronous Stochastic Gradient Descent (SSGD) 1 is the de facto DDL optimization method. Using a sufficiently large batch size is critical to achieving DDL runtime speedup. In a large batch setting, the learning rate must be incr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	269,482
2212.03327	A neural approach to synchronization in wireless networks with heterogeneous sources of noise	The paper addresses state estimation for clock synchronization in the presence of factors affecting the quality of synchronization. Examples are temperature variations and delay asymmetry. These working conditions make synchronization a challenging problem in many wireless environments, such as Wireless Sensor Networks...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	335,076
cs/9903002	An Algebraic Programming Style for Numerical Software and its Optimization	The abstract mathematical theory of partial differential equations (PDEs) is formulated in terms of manifolds, scalar fields, tensors, and the like, but these algebraic structures are hardly recognizable in actual PDE solvers. The general aim of the Sophus programming style is to bridge the gap between theory and pract...	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	540,483
2102.13355	Predicting gender and age categories in English conversations using lexical, non-lexical, and turn-taking features	This paper examines gender and age salience and (stereo)typicality in British English talk with the aim to predict gender and age categories based on lexical, phrasal and turn-taking features. We examine the SpokenBNC, a corpus of around 11.4 million words of British English conversations and identify behavioural diffe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	222,036
2306.00717	Graph Neural Networks-Based User Pairing in Wireless Communication Systems	Recently, deep neural networks have emerged as a solution to solve NP-hard wireless resource allocation problems in real-time. However, multi-layer perceptron (MLP) and convolutional neural network (CNN) structures, which are inherited from image processing tasks, are not optimized for wireless network problems. As net...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	370,134
2410.18556	Complexity Matters: Effective Dimensionality as a Measure for Adversarial Robustness	Quantifying robustness in a single measure for the purposes of model selection, development of adversarial training methods, and anticipating trends has so far been elusive. The simplest metric to consider is the number of trainable parameters in a model but this has previously been shown to be insufficient at explaini...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	501,935
2110.10103	Continual self-training with bootstrapped remixing for speech enhancement	We propose RemixIT, a simple and novel self-supervised training method for speech enhancement. The proposed method is based on a continuously self-training scheme that overcomes limitations from previous studies including assumptions for the in-domain noise distribution and having access to clean target signals. Specif...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,037
2208.09611	Weighted Maximum Entropy Inverse Reinforcement Learning	We study inverse reinforcement learning (IRL) and imitation learning (IM), the problems of recovering a reward or policy function from expert's demonstrated trajectories. We propose a new way to improve the learning process by adding a weight function to the maximum entropy framework, with the motivation of having the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	313,760
1805.00717	Entropy-based randomisation of rating networks	In the last years, due to the great diffusion of e-commerce, online rating platforms quickly became a common tool for purchase recommendations. However, instruments for their analysis did not evolve at the same speed. Indeed, interesting information about users' habits and tastes can be recovered just considering the b...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	96,496
2403.16833	Double skew cyclic codes over $\mathbb{F}_q+v\mathbb{F}_q$	In this study, in order to get better codes, we focus on double skew cyclic codes over the ring $\mathrm{R}= \mathbb{F}_q+v\mathbb{F}_q, ~v^2=v$ where $q$ is a prime power. We investigate the generator polynomials, minimal spanning sets, generator matrices, and the dual codes over the ring $\mathrm{R}$. As an implement...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	441,209
1708.04432	Knock-Knock: Acoustic Object Recognition by using Stacked Denoising Autoencoders	This paper presents a successful application of deep learning for object recognition based on acoustic data. The shortcomings of previously employed approaches where handcrafted features describing the acoustic data are being used, include limiting the capability of the found representation to be widely applicable and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,947
2110.03413	Curved Markov Chain Monte Carlo for Network Learning	We present a geometrically enhanced Markov chain Monte Carlo sampler for networks based on a discrete curvature measure defined on graphs. Specifically, we incorporate the concept of graph Forman curvature into sampling procedures on both the nodes and edges of a network explicitly, via the transition probability of th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	259,488
2208.03779	Sample hardness based gradient loss for long-tailed cervical cell detection	Due to the difficulty of cancer samples collection and annotation, cervical cancer datasets usually exhibit a long-tailed data distribution. When training a detector to detect the cancer cells in a WSI (Whole Slice Image) image captured from the TCT (Thinprep Cytology Test) specimen, head categories (e.g. normal cells ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	311,896
1606.03664	Weakly Supervised Scalable Audio Content Analysis	Audio Event Detection is an important task for content analysis of multimedia data. Most of the current works on detection of audio events is driven through supervised learning approaches. We propose a weakly supervised learning framework which can make use of the tremendous amount of web multimedia data with significa...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	57,124

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