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
2107.14738	A Self-Adaptive IoT-based Approach for Improving the Decision Making of Active Surgical Robots in Hospitals	In recent years, surgical robots have become instrumental tools for assisting surgeons in performing complex surgical procedures in hospitals. Unlike conventional surgical methods, robotic systems help surgeons, for example, to perform minimally invasive surgical procedures while enhancing the precision and control of ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	248,553
2309.17290	In search of dispersed memories: Generative diffusion models are associative memory networks	Uncovering the mechanisms behind long-term memory is one of the most fascinating open problems in neuroscience and artificial intelligence. Artificial associative memory networks have been used to formalize important aspects of biological memory. Generative diffusion models are a type of generative machine learning tec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	395,716
0909.3055	Compressive Sensing Based Opportunistic Protocol for Throughput Improvement in Wireless Networks	A key feature in the design of any MAC protocol is the throughput it can provide. In wireless networks, the channel of a user is not fixed but varies randomly. Thus, in order to maximize the throughput of the MAC protocol at any given time, only users with large channel gains should be allowed to transmit. In this pape...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,509
cmp-lg/9507010	On-line Learning of Binary Lexical Relations Using Two-dimensional Weighted Majority Algorithms	We consider the problem of learning a certain type of lexical semantic knowledge that can be expressed as a binary relation between words, such as the so-called sub-categorization of verbs (a verb-noun relation) and the compound noun phrase relation (a noun-noun relation). Specifically, we view this problem as an on-li...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,440
2404.14815	Time-aware Heterogeneous Graph Transformer with Adaptive Attention Merging for Health Event Prediction	The widespread application of Electronic Health Records (EHR) data in the medical field has led to early successes in disease risk prediction using deep learning methods. These methods typically require extensive data for training due to their large parameter sets. However, existing works do not exploit the full potent...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	448,830
2204.05075	Zero-phase angle asteroid taxonomy classification using unsupervised machine learning algorithms	We are in an era of large catalogs and, thus, statistical analysis tools for large data sets, such as machine learning, play a fundamental role. One example of such a survey is the Sloan Moving Object Catalog (MOC), which lists the astrometric and photometric information of all moving objects captured by the Sloan fiel...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	290,898
2212.13892	Cross-Dataset Propensity Estimation for Debiasing Recommender Systems	Datasets for training recommender systems are often subject to distribution shift induced by users' and recommenders' selection biases. In this paper, we study the impact of selection bias on datasets with different quantization. We then leverage two differently quantized datasets from different source distributions to...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	338,424
0905.1751	Experiment Study of Entropy Convergence of Ant Colony Optimization	Ant colony optimization (ACO) has been applied to the field of combinatorial optimization widely. But the study of convergence theory of ACO is rare under general condition. In this paper, the authors try to find the evidence to prove that entropy is related to the convergence of ACO, especially to the estimation of th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	3,668
2501.16249	Lightweight Weighted Average Ensemble Model for Pneumonia Detection in Chest X-Ray Images	Pneumonia is a leading cause of illness and death in children, underscoring the need for early and accurate detection. In this study, we propose a novel lightweight ensemble model for detecting pneumonia in children using chest X-ray images. This ensemble model integrates two pre-trained convolutional neural networks (...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	527,877
1911.11351	Distraction-Aware Feature Learning for Human Attribute Recognition via Coarse-to-Fine Attention Mechanism	Recently, Human Attribute Recognition (HAR) has become a hot topic due to its scientific challenges and application potentials, where localizing attributes is a crucial stage but not well handled. In this paper, we propose a novel deep learning approach to HAR, namely Distraction-aware HAR (Da-HAR). It enhances deep CN...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	155,091
2312.16438	Visual Spatial Attention and Proprioceptive Data-Driven Reinforcement Learning for Robust Peg-in-Hole Task Under Variable Conditions	Anchor-bolt insertion is a peg-in-hole task performed in the construction field for holes in concrete. Efforts have been made to automate this task, but the variable lighting and hole surface conditions, as well as the requirements for short setup and task execution time make the automation challenging. In this study, ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	418,384
2411.04408	Repairing Neural Networks for Safety in Robotic Systems using Predictive Models	This paper introduces a new method for safety-aware robot learning, focusing on repairing policies using predictive models. Our method combines behavioral cloning with neural network repair in a two-step supervised learning framework. It first learns a policy from expert demonstrations and then applies repair subject t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	506,259
1905.06686	On ZpZp[u, v]-additive cyclic and constacyclic codes	Let $\mathbb{Z}_{p}$ be the ring of residue classes modulo a prime $p$. The $\mathbb{Z}_{p}\mathbb{Z}_{p}[u,v]$-additive cyclic codes of length $(\alpha,\beta)$ is identify as $\mathbb{Z}_{p}[u,v][x]$-submodule of $\mathbb{Z}_{p}[x]/\langle x^{\alpha}-1\rangle \times \mathbb{Z}_{p}[u,v][x]/\langle x^{\beta}-1\rangle$ w...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	131,059
1201.2605	Autonomous Cleaning of Corrupted Scanned Documents - A Generative Modeling Approach	We study the task of cleaning scanned text documents that are strongly corrupted by dirt such as manual line strokes, spilled ink etc. We aim at autonomously removing dirt from a single letter-size page based only on the information the page contains. Our approach, therefore, has to learn character representations with...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	13,790
2305.15014	Unlocking Temporal Question Answering for Large Language Models with Tailor-Made Reasoning Logic	The temporal aspect is a significant dimension of our reality. We notice the challenge that large language models (LLMs) face when engaging in temporal reasoning. Our preliminary experiments show that methods involving the generation of intermediate reasoning steps, such as chain-of-thought and program-aided language m...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	367,395
2406.11143	Scorecards for Synthetic Medical Data Evaluation and Reporting	Although interest in synthetic medical data (SMD) for training and testing AI methods is growing, the absence of a standardized framework to evaluate its quality and applicability hinders its wider adoption. Here, we outline an evaluation framework designed to meet the unique requirements of medical applications, and i...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	true	false	464,737
1503.08895	End-To-End Memory Networks	We introduce a neural network with a recurrent attention model over a possibly large external memory. The architecture is a form of Memory Network (Weston et al., 2015) but unlike the model in that work, it is trained end-to-end, and hence requires significantly less supervision during training, making it more generall...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	41,633
2411.02412	Slicing for AI: An Online Learning Framework for Network Slicing Supporting AI Services	The forthcoming 6G networks will embrace a new realm of AI-driven services that requires innovative network slicing strategies, namely slicing for AI, which involves the creation of customized network slices to meet Quality of service (QoS) requirements of diverse AI services. This poses challenges due to time-varying ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	505,480
2204.05986	Machine Learning Security against Data Poisoning: Are We There Yet?	The recent success of machine learning (ML) has been fueled by the increasing availability of computing power and large amounts of data in many different applications. However, the trustworthiness of the resulting models can be compromised when such data is maliciously manipulated to mislead the learning process. In th...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	291,204
1906.00731	Convergence Analysis of Gradient-Based Learning with Non-Uniform Learning Rates in Non-Cooperative Multi-Agent Settings	Considering a class of gradient-based multi-agent learning algorithms in non-cooperative settings, we provide local convergence guarantees to a neighborhood of a stable local Nash equilibrium. In particular, we consider continuous games where agents learn in (i) deterministic settings with oracle access to their gradie...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	133,494
2301.02427	Mask-then-Fill: A Flexible and Effective Data Augmentation Framework for Event Extraction	We present Mask-then-Fill, a flexible and effective data augmentation framework for event extraction. Our approach allows for more flexible manipulation of text and thus can generate more diverse data while keeping the original event structure unchanged as much as possible. Specifically, it first randomly masks out an ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	339,509
1202.2564	A better Beta for the H measure of classification performance	The area under the ROC curve is widely used as a measure of performance of classification rules. However, it has recently been shown that the measure is fundamentally incoherent, in the sense that it treats the relative severities of misclassifications differently when different classifiers are used. To overcome this, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	14,287
1704.05692	A multi-method simulation of a high-frequency bus line using AnyLogic	In this work a mixed agent-based and discrete event simulation model is developed for a high frequency bus route in the Netherlands. With this model, different passenger growth scenarios can be easily evaluated. This simulation model helps policy makers to predict changes that have to be made to bus routes and planned ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	72,053
2305.17022	Joint Antenna Selection and Beamforming for Massive MIMO-enabled Over-the-Air Federated Learning	Over-the-air federated learning (OTA-FL) is an emerging technique to reduce the computation and communication overload at the PS caused by the orthogonal transmissions of the model updates in conventional federated learning (FL). This reduction is achieved at the expense of introducing aggregation error that can be eff...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	368,378
2103.14000	Fairness in Ranking: A Survey	In the past few years, there has been much work on incorporating fairness requirements into algorithmic rankers, with contributions coming from the data management, algorithms, information retrieval, and recommender systems communities. In this survey we give a systematic overview of this work, offering a broad perspec...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	226,685
2412.07120	Corrupted Learning Dynamics in Games	Learning in games refers to scenarios where multiple players interact in a shared environment, each aiming to minimize their regret. An equilibrium can be computed at a fast rate of $O(1/T)$ when all players follow the optimistic follow-the-regularized-leader (OFTRL). However, this acceleration is limited to the honest...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	515,515
2301.12652	REPLUG: Retrieval-Augmented Black-Box Language Models	We introduce REPLUG, a retrieval-augmented language modeling framework that treats the language model (LM) as a black box and augments it with a tuneable retrieval model. Unlike prior retrieval-augmented LMs that train language models with special cross attention mechanisms to encode the retrieved text, REPLUG simply p...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	342,627
2111.11595	Semi-Supervised Learning with Taxonomic Labels	We propose techniques to incorporate coarse taxonomic labels to train image classifiers in fine-grained domains. Such labels can often be obtained with a smaller effort for fine-grained domains such as the natural world where categories are organized according to a biological taxonomy. On the Semi-iNat dataset consisti...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	267,709
1902.09467	Reinforcement Learning to Minimize Age of Information with an Energy Harvesting Sensor with HARQ and Sensing Cost	The time average expected age of information (AoI) is studied for status updates sent from an energy-harvesting transmitter with a finite-capacity battery. The optimal scheduling policy is first studied under different feedback mechanisms when the channel and energy harvesting statistics are known. For the case of unkn...	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	true	122,416
2210.07271	BLOX: Macro Neural Architecture Search Benchmark and Algorithms	Neural architecture search (NAS) has been successfully used to design numerous high-performance neural networks. However, NAS is typically compute-intensive, so most existing approaches restrict the search to decide the operations and topological structure of a single block only, then the same block is stacked repeated...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	323,635
2409.07083	echemdb Toolkit -- a Lightweight Approach to Getting Data Ready for Data Management Solutions	According to the FAIR (findability, accessibility, interoperability, and reusability) principles, scientific data should always be stored with machine-readable descriptive metadata. Existing solutions to store data with metadata, such as electronic lab notebooks (ELN), are often very domain-specific and not sufficientl...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	487,377
2409.01329	Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning	Machine Learning (ML) is crucial in many sectors, including computer vision. However, ML models trained on sensitive data face security challenges, as they can be attacked and leak information. Privacy-Preserving Machine Learning (PPML) addresses this by using Differential Privacy (DP) to balance utility and privacy. T...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	485,297
1602.08357	Cortical Computation via Iterative Constructions	We study Boolean functions of an arbitrary number of input variables that can be realized by simple iterative constructions based on constant-size primitives. This restricted type of construction needs little global coordination or control and thus is a candidate for neurally feasible computation. Valiant's constructio...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	52,634
1902.04942	Sample Variance Decay in Randomly Initialized ReLU Networks	Before training a neural net, a classic rule of thumb is to randomly initialize the weights so the variance of activations is preserved across layers. This is traditionally interpreted using the total variance due to randomness in both weights \emph{and} samples. Alternatively, one can interpret the rule of thumb as pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	121,443
2311.08481	Functionality learning through specification instructions	Test suites assess natural language processing models' performance on specific functionalities: cases of interest involving model robustness, fairness, or particular linguistic capabilities. This paper introduces specification instructions: text descriptions specifying fine-grained task-specific behaviors. For each fun...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	407,741
2412.05660	Multimodal Biometric Authentication Using Camera-Based PPG and Fingerprint Fusion	Camera-based photoplethysmography (PPG) obtained from smartphones has shown great promise for personalized healthcare and secure authentication. This paper presents a multimodal biometric system that integrates PPG signals extracted from videos with fingerprint data to enhance the accuracy of user verification. The sys...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	514,918
2406.17168	Reinforcement Learning via Auxiliary Task Distillation	We present Reinforcement Learning via Auxiliary Task Distillation (AuxDistill), a new method that enables reinforcement learning (RL) to perform long-horizon robot control problems by distilling behaviors from auxiliary RL tasks. AuxDistill achieves this by concurrently carrying out multi-task RL with auxiliary tasks, ...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	467,448
1708.07732	Multi-Agent Q-Learning for Minimizing Demand-Supply Power Deficit in Microgrids	We consider the problem of minimizing the difference in the demand and the supply of power using microgrids. We setup multiple microgrids, that provide electricity to a village. They have access to the batteries that can store renewable power and also the electrical lines from the main grid. During each time period, th...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	79,517
2009.14138	Selective Cascade of Residual ExtraTrees	We propose a novel tree-based ensemble method named Selective Cascade of Residual ExtraTrees (SCORE). SCORE draws inspiration from representation learning, incorporates regularized regression with variable selection features, and utilizes boosting to improve prediction and reduce generalization errors. We also develop ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	197,949
2309.02465	Towards Foundational AI Models for Additive Manufacturing: Language Models for G-Code Debugging, Manipulation, and Comprehension	3D printing or additive manufacturing is a revolutionary technology that enables the creation of physical objects from digital models. However, the quality and accuracy of 3D printing depend on the correctness and efficiency of the G-code, a low-level numerical control programming language that instructs 3D printers ho...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	true	390,056
2004.02984	MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices	Natural Language Processing (NLP) has recently achieved great success by using huge pre-trained models with hundreds of millions of parameters. However, these models suffer from heavy model sizes and high latency such that they cannot be deployed to resource-limited mobile devices. In this paper, we propose MobileBERT ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	171,396
2409.10790	Model Tells Itself Where to Attend: Faithfulness Meets Automatic Attention Steering	Large language models (LLMs) have demonstrated remarkable performance across various real-world tasks. However, they often struggle to fully comprehend and effectively utilize their input contexts, resulting in responses that are unfaithful or hallucinated. This difficulty increases for contexts that are long or contai...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	488,882
cs/0205016	From Alife Agents to a Kingdom of N Queens	This paper presents a new approach to solving N-queen problems, which involves a model of distributed autonomous agents with artificial life (ALife) and a method of representing N-queen constraints in an agent environment. The distributed agents locally interact with their living environment, i.e., a chessboard, and ex...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	537,571
2405.17390	KSW: Khmer Stop Word based Dictionary for Keyword Extraction	This paper introduces KSW, a Khmer-specific approach to keyword extraction that leverages a specialized stop word dictionary. Due to the limited availability of natural language processing resources for the Khmer language, effective keyword extraction has been a significant challenge. KSW addresses this by developing a...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	457,884
2309.06075	A2V: A Semi-Supervised Domain Adaptation Framework for Brain Vessel Segmentation via Two-Phase Training Angiography-to-Venography Translation	We present a semi-supervised domain adaptation framework for brain vessel segmentation from different image modalities. Existing state-of-the-art methods focus on a single modality, despite the wide range of available cerebrovascular imaging techniques. This can lead to significant distribution shifts that negatively i...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	391,301
2409.18470	Fairness without Sensitive Attributes via Knowledge Sharing	While model fairness improvement has been explored previously, existing methods invariably rely on adjusting explicit sensitive attribute values in order to improve model fairness in downstream tasks. However, we observe a trend in which sensitive demographic information becomes inaccessible as public concerns around d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	492,272
1702.07158	Next Basket Prediction using Recurring Sequential Patterns	Nowadays, a hot challenge for supermarket chains is to offer personalized services for their customers. Next basket prediction, i.e., supplying the customer a shopping list for the next purchase according to her current needs, is one of these services. Current approaches are not capable to capture at the same time the ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	68,737
2208.00081	Sampling Attacks on Meta Reinforcement Learning: A Minimax Formulation and Complexity Analysis	Meta reinforcement learning (meta RL), as a combination of meta-learning ideas and reinforcement learning (RL), enables the agent to adapt to different tasks using a few samples. However, this sampling-based adaptation also makes meta RL vulnerable to adversarial attacks. By manipulating the reward feedback from sampli...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	310,730
2112.09425	Knowledge graph enhanced recommender system	Knowledge Graphs (KGs) have shown great success in recommendation. This is attributed to the rich attribute information contained in KG to improve item and user representations as side information. However, existing knowledge-aware methods leverage attribute information at a coarse-grained level both in item and user s...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	272,146
1811.10666	Art2Real: Unfolding the Reality of Artworks via Semantically-Aware Image-to-Image Translation	The applicability of computer vision to real paintings and artworks has been rarely investigated, even though a vast heritage would greatly benefit from techniques which can understand and process data from the artistic domain. This is partially due to the small amount of annotated artistic data, which is not even comp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	114,541
2106.05036	Towards Defending against Adversarial Examples via Attack-Invariant Features	Deep neural networks (DNNs) are vulnerable to adversarial noise. Their adversarial robustness can be improved by exploiting adversarial examples. However, given the continuously evolving attacks, models trained on seen types of adversarial examples generally cannot generalize well to unseen types of adversarial example...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	239,948
2308.11520	Exploring the Power of Topic Modeling Techniques in Analyzing Customer Reviews: A Comparative Analysis	The exponential growth of online social network platforms and applications has led to a staggering volume of user-generated textual content, including comments and reviews. Consequently, users often face difficulties in extracting valuable insights or relevant information from such content. To address this challenge, m...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	387,174
2401.10666	MixNet: Efficient Global Modeling for Ultra-High-Definition Image Restoration	Recent advancements in image restoration methods employing global modeling have shown promising results. However, these approaches often incur substantial memory requirements, particularly when processing ultra-high-definition (UHD) images. In this paper, we propose a novel image restoration method called MixNet, which...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	422,727
1804.09250	Reliability based-design optimization using the directional bat algorithm	Reliability based design optimization (RBDO) problems are important in engineering applications, but it is challenging to solve such problems. In this study, a new resolution method based on the directional Bat Algorithm (dBA) is presented. To overcome the difficulties in the evaluations of probabilistic constraints, t...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	95,933
1904.00129	Dance Dance Generation: Motion Transfer for Internet Videos	This work presents computational methods for transferring body movements from one person to another with videos collected in the wild. Specifically, we train a personalized model on a single video from the Internet which can generate videos of this target person driven by the motions of other people. Our model is built...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	125,799
1911.09564	Parameter-Free Locally Differentially Private Stochastic Subgradient Descent	We consider the problem of minimizing a convex risk with stochastic subgradients guaranteeing $\epsilon$-locally differentially private ($\epsilon$-LDP). While it has been shown that stochastic optimization is possible with $\epsilon$-LDP via the standard SGD (Song et al., 2013), its convergence rate largely depends on...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	154,558
2207.02907	Exploring Generative Adversarial Networks for Text-to-Image Generation with Evolution Strategies	In the context of generative models, text-to-image generation achieved impressive results in recent years. Models using different approaches were proposed and trained in huge datasets of pairs of texts and images. However, some methods rely on pre-trained models such as Generative Adversarial Networks, searching throug...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	306,652
1104.1678	A Proposed Decision Support System/Expert System for Guiding Fresh Students in Selecting a Faculty in Gomal University, Pakistan	This paper presents the design and development of a proposed rule based Decision Support System that will help students in selecting the best suitable faculty/major decision while taking admission in Gomal University, Dera Ismail Khan, Pakistan. The basic idea of our approach is to design a model for testing and measur...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	9,926
2102.00429	High Fidelity Speech Regeneration with Application to Speech Enhancement	Speech enhancement has seen great improvement in recent years mainly through contributions in denoising, speaker separation, and dereverberation methods that mostly deal with environmental effects on vocal audio. To enhance speech beyond the limitations of the original signal, we take a regeneration approach, in which ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	217,780
2310.00977	Position Sensing Errors in Synchronous Motor Drives	Non-ideal position estimation results in degraded performance of synchronous motor drive systems due to reduction of the average capability of the drive as well as torque harmonics of different orders. The signature and extent of the performance degradation is further dependent, quite significantly, on the current cont...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	396,233
2011.07011	Imposing Robust Structured Control Constraint on Reinforcement Learning of Linear Quadratic Regulator	This paper discusses learning a structured feedback control to obtain sufficient robustness to exogenous inputs for linear dynamic systems with unknown state matrix. The structural constraint on the controller is necessary for many cyber-physical systems, and our approach presents a design for any generic structure, pa...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	206,413
2212.11277	Audio Denoising for Robust Audio Fingerprinting	Music discovery services let users identify songs from short mobile recordings. These solutions are often based on Audio Fingerprinting, and rely more specifically on the extraction of spectral peaks in order to be robust to a number of distortions. Few works have been done to study the robustness of these algorithms t...	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	337,748
2212.03010	GD-MAE: Generative Decoder for MAE Pre-training on LiDAR Point Clouds	Despite the tremendous progress of Masked Autoencoders (MAE) in developing vision tasks such as image and video, exploring MAE in large-scale 3D point clouds remains challenging due to the inherent irregularity. In contrast to previous 3D MAE frameworks, which either design a complex decoder to infer masked information...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	334,966
2402.02514	Deep Supervision by Gaussian Pseudo-label-based Morphological Attention for Abdominal Aorta Segmentation in Non-Contrast CTs	The segmentation of the abdominal aorta in non-contrast CT images is a non-trivial task for computer-assisted endovascular navigation, particularly in scenarios where contrast agents are unsuitable. While state-of-the-art deep learning segmentation models have been proposed recently for this task, they are trained on m...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	426,596
2007.15101	A superconducting nanowire spiking element for neural networks	As the limits of traditional von Neumann computing come into view, the brain's ability to communicate vast quantities of information using low-power spikes has become an increasing source of inspiration for alternative architectures. Key to the success of these largescale neural networks is a power-efficient spiking el...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	189,563
1809.01816	Visual Coreference Resolution in Visual Dialog using Neural Module Networks	Visual dialog entails answering a series of questions grounded in an image, using dialog history as context. In addition to the challenges found in visual question answering (VQA), which can be seen as one-round dialog, visual dialog encompasses several more. We focus on one such problem called visual coreference resol...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	106,898
2306.16177	Defining data science: a new field of inquiry	Data science is not a science. It is a research paradigm. Its power, scope, and scale will surpass science, our most powerful research paradigm, to enable knowledge discovery and change our world. We have yet to understand and define it, vital to realizing its potential and managing its risks. Modern data science is in...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	376,304
2305.14668	NOVUM: Neural Object Volumes for Robust Object Classification	Discriminative models for object classification typically learn image-based representations that do not capture the compositional and 3D nature of objects. In this work, we show that explicitly integrating 3D compositional object representations into deep networks for image classification leads to a largely enhanced ge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	367,167
1309.7842	Difference Balanced Functions and Their Generalized Difference Sets	Difference balanced functions from $F_{q^n}^*$ to $F_q$ are closely related to combinatorial designs and naturally define $p$-ary sequences with the ideal two-level autocorrelation. In the literature, all existing such functions are associated with the $d$-homogeneous property, and it was conjectured by Gong and Song t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	27,428
2208.13442	Modeling Adaptive Fine-grained Task Relatedness for Joint CTR-CVR Estimation	In modern advertising and recommender systems, multi-task learning (MTL) paradigm has been widely employed to jointly predict diverse user feedbacks (e.g. click and purchase). While, existing MTL approaches are either rigid to adapt to different scenarios, or only capture coarse-grained task relatedness, thus making it...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	315,063
2401.02838	CrisisViT: A Robust Vision Transformer for Crisis Image Classification	In times of emergency, crisis response agencies need to quickly and accurately assess the situation on the ground in order to deploy relevant services and resources. However, authorities often have to make decisions based on limited information, as data on affected regions can be scarce until local response services ca...	false	false	false	true	true	false	false	false	false	false	false	true	false	false	false	false	false	true	419,860
2402.17645	SongComposer: A Large Language Model for Lyric and Melody Composition in Song Generation	We present SongComposer, an innovative LLM designed for song composition. It could understand and generate melodies and lyrics in symbolic song representations, by leveraging the capability of LLM. Existing music-related LLM treated the music as quantized audio signals, while such implicit encoding leads to inefficient...	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	433,082
2405.18087	FlowSDF: Flow Matching for Medical Image Segmentation Using Distance Transforms	Medical image segmentation plays an important role in accurately identifying and isolating regions of interest within medical images. Generative approaches are particularly effective in modeling the statistical properties of segmentation masks that are closely related to the respective structures. In this work we intro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	458,273
2407.06317	Enhanced Safety in Autonomous Driving: Integrating Latent State Diffusion Model for End-to-End Navigation	With the advancement of autonomous driving, ensuring safety during motion planning and navigation is becoming more and more important. However, most end-to-end planning methods suffer from a lack of safety. This research addresses the safety issue in the control optimization problem of autonomous driving, formulated as...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	471,353
1111.0054	CTL Model Update for System Modifications	Model checking is a promising technology, which has been applied for verification of many hardware and software systems. In this paper, we introduce the concept of model update towards the development of an automatic system modification tool that extends model checking functions. We define primitive update operations o...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	12,850
1402.2793	Computing Agents for Decision Support Systems	In decision support systems, it is essential to get a candidate solution fast, even if it means resorting to an approximation. This constraint introduces a scalability requirement with regard to the kind of heuristics which can be used in such systems. As execution time is bounded, these algorithms need to give better ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	30,816
1710.10498	Topic Based Sentiment Analysis Using Deep Learning	In this paper , we tackle Sentiment Analysis conditioned on a Topic in Twitter data using Deep Learning . We propose a 2-tier approach : In the first phase we create our own Word Embeddings and see that they do perform better than state-of-the-art embeddings when used with standard classifiers. We then perform inferenc...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	83,394
2202.13959	Semi-Structured Query Grounding for Document-Oriented Databases with Deep Retrieval and Its Application to Receipt and POI Matching	Semi-structured query systems for document-oriented databases have many real applications. One particular application that we are interested in is matching each financial receipt image with its corresponding place of interest (POI, e.g., restaurant) in the nationwide database. The problem is especially challenging in t...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	282,805
1703.10622	Diving into the shallows: a computational perspective on large-scale shallow learning	In this paper we first identify a basic limitation in gradient descent-based optimization methods when used in conjunctions with smooth kernels. An analysis based on the spectral properties of the kernel demonstrates that only a vanishingly small portion of the function space is reachable after a polynomial number of g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	70,942
1610.00175	Near-Infrared Image Dehazing Via Color Regularization	Near-infrared imaging can capture haze-free near-infrared gray images and visible color images, according to physical scattering models, e.g., Rayleigh or Mie models. However, there exist serious discrepancies in brightness and image structures between the near-infrared gray images and the visible color images. The dir...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	61,800
2003.08860	Adaptive motion control of parallel robots with kinematic and dynamic uncertainties	One of the most challenging issues in adaptive control of robot manipulators with kinematic uncertainties is requirement of the inverse of Jacobian matrix in regressor form. This requirement is inevitable in the case of the control of parallel robots, whose dynamic equations are written directly in the task space. In t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	168,892
1902.06377	SCEF: A Support-Confidence-aware Embedding Framework for Knowledge Graph Refinement	Knowledge graph (KG) refinement mainly aims at KG completion and correction (i.e., error detection). However, most conventional KG embedding models only focus on KG completion with an unreasonable assumption that all facts in KG hold without noises, ignoring error detection which also should be significant and essentia...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	121,752
2101.10573	Representations for Question Answering from Documents with Tables and Text	Tables in Web documents are pervasive and can be directly used to answer many of the queries searched on the Web, motivating their integration in question answering. Very often information presented in tables is succinct and hard to interpret with standard language representations. On the other hand, tables often appea...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	216,987
2308.15822	AMDNet23: A combined deep Contour-based Convolutional Neural Network and Long Short Term Memory system to diagnose Age-related Macular Degeneration	In light of the expanding population, an automated framework of disease detection can assist doctors in the diagnosis of ocular diseases, yields accurate, stable, rapid outcomes, and improves the success rate of early detection. The work initially intended the enhancing the quality of fundus images by employing an adap...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	388,806
1603.00751	Equity forecast: Predicting long term stock price movement using machine learning	Long term investment is one of the major investment strategies. However, calculating intrinsic value of some company and evaluating shares for long term investment is not easy, since analyst have to care about a large number of financial indicators and evaluate them in a right manner. So far, little help in predicting ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	52,810
2202.01375	Resource Management and Security Scheme of ICPSs and IoT Based on VNE Algorithm	The development of Intelligent Cyber-Physical Systems (ICPSs) in virtual network environment is facing severe challenges. On the one hand, the Internet of things (IoT) based on ICPSs construction needs a large amount of reasonable network resources support. On the other hand, ICPSs are facing severe network security pr...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	278,462
1707.06729	Predictive networking and optimization for flow-based networks	Artificial Neural Networks (ANNs) were used to classify neural network flows by flow size. After training the neural network was able to predict the size of a flows with 87% accuracy with a Feed Forward Neural Network. This demonstrates that flow based routers can prioritize candidate flows with a predicted large numbe...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	77,474
2202.04075	Joint-bone Fusion Graph Convolutional Network for Semi-supervised Skeleton Action Recognition	In recent years, graph convolutional networks (GCNs) play an increasingly critical role in skeleton-based human action recognition. However, most GCN-based methods still have two main limitations: 1) They only consider the motion information of the joints or process the joints and bones separately, which are unable to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	279,449
2410.03978	Optimizing Sparse Generalized Singular Vectors for Feature Selection in Proximal Support Vector Machines with Application to Breast and Ovarian Cancer Detection	This paper presents approaches to compute sparse solutions of Generalized Singular Value Problem (GSVP). The GSVP is regularized by $\ell_1$-norm and $\ell_q$-penalty for $0<q<1$, resulting in the $\ell_1$-GSVP and $\ell_q$-GSVP formulations. The solutions of these problems are determined by applying the proximal gradi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	495,072
2004.11935	The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget	In many applications, it is desirable to extract only the relevant information from complex input data, which involves making a decision about which input features are relevant. The information bottleneck method formalizes this as an information-theoretic optimization problem by maintaining an optimal tradeoff between ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	174,068
1608.03866	Distributed Optimization for Client-Server Architecture with Negative Gradient Weights	Availability of both massive datasets and computing resources have made machine learning and predictive analytics extremely pervasive. In this work we present a synchronous algorithm and architecture for distributed optimization motivated by privacy requirements posed by applications in machine learning. We present an ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	59,739
1406.2464	Music and Vocal Separation Using Multi-Band Modulation Based Features	The potential use of non-linear speech features has not been investigated for music analysis although other commonly used speech features like Mel Frequency Ceptral Coefficients (MFCC) and pitch have been used extensively. In this paper, we assume an audio signal to be a sum of modulated sinusoidal and then use the ene...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	33,749
1605.06177	Fine-Grained Classification of Pedestrians in Video: Benchmark and State of the Art	A video dataset that is designed to study fine-grained categorisation of pedestrians is introduced. Pedestrians were recorded "in-the-wild" from a moving vehicle. Annotations include bounding boxes, tracks, 14 keypoints with occlusion information and the fine-grained categories of age (5 classes), sex (2 classes), weig...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	56,093
2210.01111	MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples	Multi-label classification, which predicts a set of labels for an input, has many applications. However, multiple recent studies showed that multi-label classification is vulnerable to adversarial examples. In particular, an attacker can manipulate the labels predicted by a multi-label classifier for an input via addin...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	321,133
2502.00265	RADx Data Hub: A Cloud Platform for FAIR, Harmonized COVID-19 Data	The COVID-19 pandemic highlighted the urgent need for robust systems to enable rapid data collection, integration, and analysis for public health responses. Existing approaches often relied on disparate, non-interoperable systems, creating bottlenecks in comprehensive analyses and timely decision-making. To address the...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	529,283
1804.07573	MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile Devices	We present a class of extremely efficient CNN models, MobileFaceNets, which use less than 1 million parameters and are specifically tailored for high-accuracy real-time face verification on mobile and embedded devices. We first make a simple analysis on the weakness of common mobile networks for face verification. The ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	95,552
1203.2936	Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm	The least absolute shrinkage and selection operator (LASSO) for linear regression exploits the geometric interplay of the $\ell_2$-data error objective and the $\ell_1$-norm constraint to arbitrarily select sparse models. Guiding this uninformed selection process with sparsity models has been precisely the center of at...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	14,864
1904.01191	Planning with Expectation Models	Distribution and sample models are two popular model choices in model-based reinforcement learning (MBRL). However, learning these models can be intractable, particularly when the state and action spaces are large. Expectation models, on the other hand, are relatively easier to learn due to their compactness and have a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	126,081
2004.10522	Practical calibration of the temperature parameter in Gibbs posteriors	PAC-Bayesian algorithms and Gibbs posteriors are gaining popularity due to their robustness against model misspecification even when Bayesian inference is inconsistent. The PAC-Bayesian alpha-posterior is a generalization of the standard Bayes posterior which can be tempered with a parameter alpha to handle inconsisten...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	173,658
2307.09025	qecGPT: decoding Quantum Error-correcting Codes with Generative Pre-trained Transformers	We propose a general framework for decoding quantum error-correcting codes with generative modeling. The model utilizes autoregressive neural networks, specifically Transformers, to learn the joint probability of logical operators and syndromes. This training is in an unsupervised way, without the need for labeled trai...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	380,031

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