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
1305.3586	Utility Optimal Scheduling and Admission Control for Adaptive Video Streaming in Small Cell Networks	We consider the jointly optimal design of a transmission scheduling and admission control policy for adaptive video streaming over small cell networks. We formulate the problem as a dynamic network utility maximization and observe that it naturally decomposes into two subproblems: admission control and transmission sch...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	24,618
2310.00653	Reformulating Vision-Language Foundation Models and Datasets Towards Universal Multimodal Assistants	Recent Multimodal Large Language Models (MLLMs) exhibit impressive abilities to perceive images and follow open-ended instructions. The capabilities of MLLMs depend on two crucial factors: the model architecture to facilitate the feature alignment of visual modules and large language models; the multimodal instruction ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	396,079
2101.11302	Multilingual and cross-lingual document classification: A meta-learning approach	The great majority of languages in the world are considered under-resourced for the successful application of deep learning methods. In this work, we propose a meta-learning approach to document classification in limited-resource setting and demonstrate its effectiveness in two different settings: few-shot, cross-lingu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	217,230
1611.04687	Intrinsic Geometric Information Transfer Learning on Multiple Graph-Structured Datasets	Graphs provide a powerful means for representing complex interactions between entities. Recently, deep learning approaches are emerging for representing and modeling graph-structured data, although the conventional deep learning methods (such as convolutional neural networks and recurrent neural networks) have mainly f...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	63,885
2401.15864	Spatial Decomposition and Temporal Fusion based Inter Prediction for Learned Video Compression	Video compression performance is closely related to the accuracy of inter prediction. It tends to be difficult to obtain accurate inter prediction for the local video regions with inconsistent motion and occlusion. Traditional video coding standards propose various technologies to handle motion inconsistency and occlus...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	424,618
2301.12012	In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States	Learning-based control approaches have shown great promise in performing complex tasks directly from high-dimensional perception data for real robotic systems. Nonetheless, the learned controllers can behave unexpectedly if the trajectories of the system divert from the training data distribution, which can compromise ...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	342,349
1611.04654	Asymptotic Performance Analysis of Majority Sentiment Detection in Online Social Networks	We analyze the problem of majority sentiment detection in Online Social Networks (OSN), and relate the detection error probability to the underlying graph of the OSN. Modeling the underlying social network as an Ising Markov random field prior based on a given graph, we show that in the case of the empty graph (indepen...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	63,878
2011.07980	Spherical convolutions on molecular graphs for protein model quality assessment	Processing information on 3D objects requires methods stable to rigid-body transformations, in particular rotations, of the input data. In image processing tasks, convolutional neural networks achieve this property using rotation-equivariant operations. However, contrary to images, graphs generally have irregular topol...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	206,731
2401.01887	LEAP-VO: Long-term Effective Any Point Tracking for Visual Odometry	Visual odometry estimates the motion of a moving camera based on visual input. Existing methods, mostly focusing on two-view point tracking, often ignore the rich temporal context in the image sequence, thereby overlooking the global motion patterns and providing no assessment of the full trajectory reliability. These ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	419,535
1701.08259	Detection, Segmentation and Recognition of Face and its Features Using Neural Network	Face detection and recognition has been prevalent with research scholars and diverse approaches have been incorporated till date to serve purpose. The rampant advent of biometric analysis systems, which may be full body scanners, or iris detection and recognition systems and the finger print recognition systems, and su...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	67,431
1906.02778	Active Deep Decoding of Linear Codes	High quality data is essential in deep learning to train a robust model. While in other fields data is sparse and costly to collect, in error decoding it is free to query and label thus allowing potential data exploitation. Utilizing this fact and inspired by active learning, two novel methods are introduced to improve...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	134,172
2304.03973	RobCaps: Evaluating the Robustness of Capsule Networks against Affine Transformations and Adversarial Attacks	Capsule Networks (CapsNets) are able to hierarchically preserve the pose relationships between multiple objects for image classification tasks. Other than achieving high accuracy, another relevant factor in deploying CapsNets in safety-critical applications is the robustness against input transformations and malicious ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	357,016
1810.03102	A Fast Text Similarity Measure for Large Document Collections using Multi-reference Cosine and Genetic Algorithm	One of the important factors that make a search engine fast and accurate is a concise and duplicate free index. In order to remove duplicate and near-duplicate documents from the index, a search engine needs a swift and reliable duplicate and near-duplicate text document detection system. Traditional approaches to this...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	109,737
2408.12709	Autonomous Grid-Forming Inverter Exponential Droop Control for Improved Frequency Stability	This paper introduces the novel Droop-e grid-forming power electronic converter control strategy, which establishes a non-linear, active power--frequency droop relationship based on an exponential function of the power output. A primary advantage of Droop-e is an increased utilization of available power headroom that d...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	482,850
2401.12995	Harmonizing Code-mixed Conversations: Personality-assisted Code-mixed Response Generation in Dialogues	Code-mixing, the blending of multiple languages within a single conversation, introduces a distinctive challenge, particularly in the context of response generation. Capturing the intricacies of code-mixing proves to be a formidable task, given the wide-ranging variations influenced by individual speaking styles and cu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	423,577
2403.06396	A Segmentation Foundation Model for Diverse-type Tumors	Large pre-trained models with their numerous model parameters and extensive training datasets have shown excellent performance in various tasks. Many publicly available medical image datasets do not have a sufficient amount of data so there are few large-scale models in medical imaging. We propose a large-scale Tumor S...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,427
2011.11487	Verifying the Correctness of Analytic Query Results	Data outsourcing is a cost-effective solution for data owners to tackle issues such as large volumes of data, huge number of users, and intensive computation needed for data analysis. They can simply upload their databases to a cloud and let it perform all management works, including query processing. One problem with ...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	207,840
2007.12421	Micro-expression spotting: A new benchmark	Micro-expressions (MEs) are brief and involuntary facial expressions that occur when people are trying to hide their true feelings or conceal their emotions. Based on psychology research, MEs play an important role in understanding genuine emotions, which leads to many potential applications. Therefore, ME analysis has...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,819
2303.01330	Continuous Implicit SDF Based Any-shape Robot Trajectory Optimization	Optimization-based trajectory generation methods are widely used in whole-body planning for robots. However, existing work either oversimplifies the robot's geometry and environment representation, resulting in a conservative trajectory, or suffers from a huge overhead in maintaining additional information such as the ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	348,926
2303.10216	Approximation of group explainers with coalition structure using Monte Carlo sampling on the product space of coalitions and features	In recent years, many Machine Learning (ML) explanation techniques have been designed using ideas from cooperative game theory. These game-theoretic explainers suffer from high complexity, hindering their exact computation in practical settings. In our work, we focus on a wide class of linear game values, as well as co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	352,352
2212.11078	C2F-TCN: A Framework for Semi and Fully Supervised Temporal Action Segmentation	Temporal action segmentation tags action labels for every frame in an input untrimmed video containing multiple actions in a sequence. For the task of temporal action segmentation, we propose an encoder-decoder-style architecture named C2F-TCN featuring a "coarse-to-fine" ensemble of decoder outputs. The C2F-TCN framew...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	337,683
2406.09765	Application of Natural Language Processing in Financial Risk Detection	This paper explores the application of Natural Language Processing (NLP) in financial risk detection. By constructing an NLP-based financial risk detection model, this study aims to identify and predict potential risks in financial documents and communications. First, the fundamental concepts of NLP and its theoretical...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	464,073
1410.4426	Partial Force Control of Constrained Floating-Base Robots	Legged robots are typically in rigid contact with the environment at multiple locations, which add a degree of complexity to their control. We present a method to control the motion and a subset of the contact forces of a floating-base robot. We derive a new formulation of the lexicographic optimization problem typical...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	36,803
1910.01671	Pure and Spurious Critical Points: a Geometric Study of Linear Networks	The critical locus of the loss function of a neural network is determined by the geometry of the functional space and by the parameterization of this space by the network's weights. We introduce a natural distinction between pure critical points, which only depend on the functional space, and spurious critical points, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	147,996
1805.08263	Learning What Information to Give in Partially Observed Domains	In many robotic applications, an autonomous agent must act within and explore a partially observed environment that is unobserved by its human teammate. We consider such a setting in which the agent can, while acting, transmit declarative information to the human that helps them understand aspects of this unseen enviro...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	98,084
2401.04235	High-precision Voice Search Query Correction via Retrievable Speech-text Embedings	Automatic speech recognition (ASR) systems can suffer from poor recall for various reasons, such as noisy audio, lack of sufficient training data, etc. Previous work has shown that recall can be improved by retrieving rewrite candidates from a large database of likely, contextually-relevant alternatives to the hypoth...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	420,365
1805.03225	A Mixed Classification-Regression Framework for 3D Pose Estimation from 2D Images	3D pose estimation from a single 2D image is an important and challenging task in computer vision with applications in autonomous driving, robot manipulation and augmented reality. Since 3D pose is a continuous quantity, a natural formulation for this task is to solve a pose regression problem. However, since pose regr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	97,005
1804.02608	Penetrating a Social Network: The Follow-back Problem	Modern threats have emerged from the prevalence of social networks. Hostile actors, such as extremist groups or foreign governments, utilize these networks to run propaganda campaigns with different aims. For extremists, these campaigns are designed for recruiting new members or inciting violence. For foreign governmen...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	94,444
1706.00536	Modeling Latent Attention Within Neural Networks	Deep neural networks are able to solve tasks across a variety of domains and modalities of data. Despite many empirical successes, we lack the ability to clearly understand and interpret the learned internal mechanisms that contribute to such effective behaviors or, more critically, failure modes. In this work, we pres...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	74,639
2202.02894	Effects of Parametric and Non-Parametric Methods on High Dimensional Sparse Matrix Representations	The semantics are derived from textual data that provide representations for Machine Learning algorithms. These representations are interpretable form of high dimensional sparse matrix that are given as an input to the machine learning algorithms. Since learning methods are broadly classified as parametric and non-para...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,990
1910.07995	Hybrid Fuzzy Control of Nonlinear Inverted Pendulum System	Complexity and nonlinear behaviours of inverted pendulum system make its control design a very challenging task. In this paper, a hybrid fuzzy adaptive control system using model reference approach is designed for inverted-pendulum system control. The proposed method is developed to achieve position control and later s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	149,752
2405.17618	Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales	Reinforcement learning (RL) training is inherently unstable due to factors such as moving targets and high gradient variance. Reinforcement Learning from Human Feedback (RLHF) and Reinforcement Learning from AI Feedback (RLAIF) can introduce additional difficulty. Differing preferences can complicate the alignment proc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	458,028
2010.12797	Collaborative Machine Learning with Incentive-Aware Model Rewards	Collaborative machine learning (ML) is an appealing paradigm to build high-quality ML models by training on the aggregated data from many parties. However, these parties are only willing to share their data when given enough incentives, such as a guaranteed fair reward based on their contributions. This motivates the n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	true	202,859
2106.09234	Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model	Denoising is the essential step for distant supervision based named entity recognition. Previous denoising methods are mostly based on instance-level confidence statistics, which ignore the variety of the underlying noise distribution on different datasets and entity types. This makes them difficult to be adapted to hi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	241,591
2102.11228	Subspace-Based Feature Fusion From Hyperspectral And Multispectral Image For Land Cover Classification	In remote sensing, hyperspectral (HS) and multispectral (MS) image fusion have emerged as a synthesis tool to improve the data set resolution. However, conventional image fusion methods typically degrade the performance of the land cover classification. In this paper, a feature fusion method from HS and MS images for p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	221,359
2203.03893	Towards Large-Scale Relative Localization in Multi-Robot Systems with Dynamic UWB Role Allocation	Ultra-wideband (UWB) ranging has emerged as a key radio technology for robot positioning and relative localization in multi-robot systems. Multiple works are now advancing towards more scalable systems, but challenges still remain. This paper proposes a novel approach to relative localization in multi-robot systems whe...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	284,266
2011.09769	Data-Driven Robust Optimization using Unsupervised Deep Learning	Robust optimization has been established as a leading methodology to approach decision problems under uncertainty. To derive a robust optimization model, a central ingredient is to identify a suitable model for uncertainty, which is called the uncertainty set. An ongoing challenge in the recent literature is to derive ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	207,299
2401.08261	Probabilistically Robust Watermarking of Neural Networks	As deep learning (DL) models are widely and effectively used in Machine Learning as a Service (MLaaS) platforms, there is a rapidly growing interest in DL watermarking techniques that can be used to confirm the ownership of a particular model. Unfortunately, these methods usually produce watermarks susceptible to model...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	421,828
1802.04431	Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding	As spacecraft send back increasing amounts of telemetry data, improved anomaly detection systems are needed to lessen the monitoring burden placed on operations engineers and reduce operational risk. Current spacecraft monitoring systems only target a subset of anomaly types and often require costly expert knowledge to...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	90,219
2304.00006	Bi-directional personalization reinforcement learning-based architecture with active learning using a multi-model data service for the travel nursing industry	The challenges of using inadequate online recruitment systems can be addressed with machine learning and software engineering techniques. Bi-directional personalization reinforcement learning-based architecture with active learning can get recruiters to recommend qualified applicants and also enable applicants to recei...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	355,523
1208.0432	Efficient Point-to-Subspace Query in $\ell^1$ with Application to Robust Object Instance Recognition	Motivated by vision tasks such as robust face and object recognition, we consider the following general problem: given a collection of low-dimensional linear subspaces in a high-dimensional ambient (image) space, and a query point (image), efficiently determine the nearest subspace to the query in $\ell^1$ distance. In...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	17,915
2210.00801	Design of the PID temperature controller for an alkaline electrolysis system with time delays	Electrolysis systems use proportional-integral-derivative (PID) temperature controllers to maintain stack temperatures around set points. However, heat transfer delays in electrolysis systems cause manual tuning of PID temperature controllers to be time-consuming, and temperature oscillations often occur. This paper fo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	321,008
1909.04102	LIC-Fusion: LiDAR-Inertial-Camera Odometry	This paper presents a tightly-coupled multi-sensor fusion algorithm termed LiDAR-inertial-camera fusion (LIC-Fusion), which efficiently fuses IMU measurements, sparse visual features, and extracted LiDAR points. In particular, the proposed LIC-Fusion performs online spatial and temporal sensor calibration between all t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	144,691
2110.04663	Learning to Control Complex Robots Using High-Dimensional Interfaces: Preliminary Insights	Human body motions can be captured as a high-dimensional continuous signal using motion sensor technologies. The resulting data can be surprisingly rich in information, even when captured from persons with limited mobility. In this work, we explore the use of limited upper-body motions, captured via motion sensors, as ...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	259,989
1904.12072	Flow-based generative models for Markov chain Monte Carlo in lattice field theory	A Markov chain update scheme using a machine-learned flow-based generative model is proposed for Monte Carlo sampling in lattice field theories. The generative model may be optimized (trained) to produce samples from a distribution approximating the desired Boltzmann distribution determined by the lattice action of the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	129,008
2402.16912	An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection	As cyber-attacks become more sophisticated, improving the robustness of Machine Learning (ML) models must be a priority for enterprises of all sizes. To reliably compare the robustness of different ML models for cyber-attack detection in enterprise computer networks, they must be evaluated in standardized conditions. T...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	432,769
1904.02520	Deep Multi-scale Discriminative Networks for Double JPEG Compression Forensics	As JPEG is the most widely used image format, the importance of tampering detection for JPEG images in blind forensics is self-evident. In this area, extracting effective statistical characteristics from a JPEG image for classification remains a challenge. Effective features are designed manually in traditional methods...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,453
2204.09498	Backdooring Explainable Machine Learning	Explainable machine learning holds great potential for analyzing and understanding learning-based systems. These methods can, however, be manipulated to present unfaithful explanations, giving rise to powerful and stealthy adversaries. In this paper, we demonstrate blinding attacks that can fully disguise an ongoing at...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	292,459
1612.03551	Reading Comprehension using Entity-based Memory Network	This paper introduces a novel neural network model for question answering, the \emph{entity-based memory network}. It enhances neural networks' ability of representing and calculating information over a long period by keeping records of entities contained in text. The core component is a memory pool which comprises ent...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	65,393
2109.05558	CoG: a Two-View Co-training Framework for Defending Adversarial Attacks on Graph	Graph neural networks exhibit remarkable performance in graph data analysis. However, the robustness of GNN models remains a challenge. As a result, they are not reliable enough to be deployed in critical applications. Recent studies demonstrate that GNNs could be easily fooled with adversarial perturbations, especiall...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	254,841
2402.10202	Bridging Associative Memory and Probabilistic Modeling	Associative memory and probabilistic modeling are two fundamental topics in artificial intelligence. The first studies recurrent neural networks designed to denoise, complete and retrieve data, whereas the second studies learning and sampling from probability distributions. Based on the observation that associative mem...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	429,866
2012.13470	GIS-Based Estimation of Seasonal Solar Energy Potential for Parking Lots and Roads	The amount of sun cast on roads and parking lots determines the charging opportunities for solar vehicles and impacts the efficiency of conventional vehicles. Estimates of solar energy potential on urban surfaces to assess parking and driving conditions need to account for the shadows cast by surrounding trees and buil...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	213,226
2009.08061	Certifying Confidence via Randomized Smoothing	Randomized smoothing has been shown to provide good certified-robustness guarantees for high-dimensional classification problems. It uses the probabilities of predicting the top two most-likely classes around an input point under a smoothing distribution to generate a certified radius for a classifier's prediction. How...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	196,120
2103.11388	Collaborative Agent Gameplay in the Pandemic Board Game	While artificial intelligence has been applied to control players' decisions in board games for over half a century, little attention is given to games with no player competition. Pandemic is an exemplar collaborative board game where all players coordinate to overcome challenges posed by events occurring during the ga...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	225,792
2210.16544	Better Lightweight Network for Free: Codeword Mimic Learning for Massive MIMO CSI feedback	The channel state information (CSI) needs to be fed back from the user equipment (UE) to the base station (BS) in frequency division duplexing (FDD) multiple-input multiple-output (MIMO) system. Recently, neural networks are widely applied to CSI compressed feedback since the original overhead is too large for the mass...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	327,374
1708.01354	CASSL: Curriculum Accelerated Self-Supervised Learning	Recent self-supervised learning approaches focus on using a few thousand data points to learn policies for high-level, low-dimensional action spaces. However, scaling this framework for high-dimensional control require either scaling up the data collection efforts or using a clever sampling strategy for training. We pr...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	78,369
2312.15098	Unsupervised Auditory and Semantic Entrainment Models with Deep Neural Networks	Speakers tend to engage in adaptive behavior, known as entrainment, when they become similar to their interlocutor in various aspects of speaking. We present an unsupervised deep learning framework that derives meaningful representation from textual features for developing semantic entrainment. We investigate the model...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	417,868
2011.13843	SFTrack++: A Fast Learnable Spectral Segmentation Approach for Space-Time Consistent Tracking	We propose an object tracking method, SFTrack++, that smoothly learns to preserve the tracked object consistency over space and time dimensions by taking a spectral clustering approach over the graph of pixels from the video, using a fast 3D filtering formulation for finding the principal eigenvector of this graph's ad...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	208,601
2007.02269	Rethinking Bottleneck Structure for Efficient Mobile Network Design	The inverted residual block is dominating architecture design for mobile networks recently. It changes the classic residual bottleneck by introducing two design rules: learning inverted residuals and using linear bottlenecks. In this paper, we rethink the necessity of such design changes and find it may bring risks of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	185,691
2302.09276	Transformer-Based Neural Marked Spatio Temporal Point Process Model for Football Match Events Analysis	With recently available football match event data that record the details of football matches, analysts and researchers have a great opportunity to develop new performance metrics, gain insight, and evaluate key performance. However, most sports sequential events modeling methods and performance metrics approaches coul...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	346,352
2003.05385	hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition	We formulate a general framework for hp-variational physics-informed neural networks (hp-VPINNs) based on the nonlinear approximation of shallow and deep neural networks and hp-refinement via domain decomposition and projection onto space of high-order polynomials. The trial space is the space of neural network, which ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	167,842
2203.06278	Distributed Dual Quaternion Based Localization of Visual Sensor Networks	In this paper we consider the localization problem for a visual sensor network. Inspired by the alternate attitude and position distributed optimization framework discussed in [1], we propose an estimation scheme that exploits the unit dual quaternion algebra to describe the sensors pose. This representation is benefic...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	285,055
2008.11149	Spatiotemporal Action Recognition in Restaurant Videos	Spatiotemporal action recognition is the task of locating and classifying actions in videos. Our project applies this task to analyzing video footage of restaurant workers preparing food, for which potential applications include automated checkout and inventory management. Such videos are quite different from the stand...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	193,190
1902.09357	CFM-BD: a distributed rule induction algorithm for building Compact Fuzzy Models in Big Data classification problems	Interpretability has always been a major concern for fuzzy rule-based classifiers. The usage of human-readable models allows them to explain the reasoning behind their predictions and decisions. However, when it comes to Big Data classification problems, fuzzy rule-based classifiers have not been able to maintain the g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	122,398
2007.10778	Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning Approach	Few-shot learning is a challenging problem that has attracted more and more attention recently since abundant training samples are difficult to obtain in practical applications. Meta-learning has been proposed to address this issue, which focuses on quickly adapting a predictor as a base-learner to new tasks, given lim...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	188,369
2106.14977	The Food Recognition Benchmark: Using DeepLearning to Recognize Food on Images	The automatic recognition of food on images has numerous interesting applications, including nutritional tracking in medical cohorts. The problem has received significant research attention, but an ongoing public benchmark to develop open and reproducible algorithms has been missing. Here, we report on the setup of suc...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	243,567
1911.04862	An End-to-end Approach for Lexical Stress Detection based on Transformer	The dominant automatic lexical stress detection method is to split the utterance into syllable segments using phoneme sequence and their time-aligned boundaries. Then we extract features from syllable to use classification method to classify the lexical stress. However, we can't get very accurate time boundaries of eac...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	153,092
2502.06314	From Pixels to Components: Eigenvector Masking for Visual Representation Learning	Predicting masked from visible parts of an image is a powerful self-supervised approach for visual representation learning. However, the common practice of masking random patches of pixels exhibits certain failure modes, which can prevent learning meaningful high-level features, as required for downstream tasks. We pro...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	532,031
2404.14956	DAWN: Domain-Adaptive Weakly Supervised Nuclei Segmentation via Cross-Task Interactions	Weakly supervised segmentation methods have gained significant attention due to their ability to reduce the reliance on costly pixel-level annotations during model training. However, the current weakly supervised nuclei segmentation approaches typically follow a two-stage pseudo-label generation and network training pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	448,884
2310.14977	Probabilistic Counting in Generalized Turnstile Models	Traditionally in the turnstile model of data streams, there is a state vector $x=(x_1,x_2,\ldots,x_n)$ which is updated through a stream of pairs $(i,k)$ where $i\in [n]$ and $k\in \Z$. Upon receiving $(i,k)$, $x_i\gets x_i + k$. A distinct count algorithm in the turnstile model takes one pass of the stream and then es...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	402,107
2411.18306	Delineating Feminist Studies through bibliometric analysis	The multidisciplinary and socially anchored nature of Feminist Studies presents unique challenges for bibliometric analysis, as this research area transcends traditional disciplinary boundaries and reflects discussions from feminist and LGBTQIA+ social movements. This paper proposes a novel approach for identifying gen...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	511,824
1503.01531	Spectral Clustering by Ellipsoid and Its Connection to Separable Nonnegative Matrix Factorization	This paper proposes a variant of the normalized cut algorithm for spectral clustering. Although the normalized cut algorithm applies the K-means algorithm to the eigenvectors of a normalized graph Laplacian for finding clusters, our algorithm instead uses a minimum volume enclosing ellipsoid for them. We show that the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	40,839
2007.01719	Ensemble Regression Models for Software Development Effort Estimation: A Comparative Study	As demand for computer software continually increases, software scope and complexity become higher than ever. The software industry is in real need of accurate estimates of the project under development. Software development effort estimation is one of the main processes in software project management. However, overest...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	185,516
1804.08316	Bilingual Embeddings with Random Walks over Multilingual Wordnets	Bilingual word embeddings represent words of two languages in the same space, and allow to transfer knowledge from one language to the other without machine translation. The main approach is to train monolingual embeddings first and then map them using bilingual dictionaries. In this work, we present a novel method to ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	95,744
2312.12660	Is post-editing really faster than human translation?	Time efficiency is paramount for the localisation industry, which demands ever-faster turnaround times. However, translation speed is largely underresearched, and there is a lack of clarity about how language service providers (LSPs) can evaluate the performance of their post-editing (PE) and human translation (HT) ser...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	417,043
2404.18624	Do Vision & Language Decoders use Images and Text equally? How Self-consistent are their Explanations?	Vision and language model (VLM) decoders are currently the best-performing architectures on multimodal tasks. Next to answers, they are able to produce natural language explanations, either in post-hoc or CoT settings. However, it is not clear to what extent they are using the input vision and text modalities when gene...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	450,334
2106.11943	Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes	Optimization algorithms such as projected Newton's method, FISTA, mirror descent, and its variants enjoy near-optimal regret bounds and convergence rates, but suffer from a computational bottleneck of computing ``projections'' in potentially each iteration (e.g., $O(T^{1/2})$ regret of online mirror descent). On the ot...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	242,568
2212.11890	Decoding surface codes with deep reinforcement learning and probabilistic policy reuse	Quantum computing (QC) promises significant advantages on certain hard computational tasks over classical computers. However, current quantum hardware, also known as noisy intermediate-scale quantum computers (NISQ), are still unable to carry out computations faithfully mainly because of the lack of quantum error corre...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	true	337,912
2004.03125	RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases	Text-to-SQL is the problem of converting a user question into an SQL query, when the question and database are given. In this paper, we present a neural network approach called RYANSQL (Recursively Yielding Annotation Network for SQL) to solve complex Text-to-SQL tasks for cross-domain databases. State-ment Position Co...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	171,456
2305.06004	Safe motion planning with environment uncertainty	We present an approach for safe motion planning under robot state and environment (obstacle and landmark location) uncertainties. To this end, we first develop an approach that accounts for the landmark uncertainties during robot localization. Existing planning approaches assume that the landmark locations are well kno...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	363,374
2502.02060	CH-MARL: Constrained Hierarchical Multiagent Reinforcement Learning for Sustainable Maritime Logistics	Addressing global challenges such as greenhouse gas emissions and resource inequity demands advanced AI-driven coordination among autonomous agents. We propose CH-MARL (Constrained Hierarchical Multiagent Reinforcement Learning), a novel framework that integrates hierarchical decision-making with dynamic constraint enf...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	530,163
1510.03055	A Diversity-Promoting Objective Function for Neural Conversation Models	Sequence-to-sequence neural network models for generation of conversational responses tend to generate safe, commonplace responses (e.g., "I don't know") regardless of the input. We suggest that the traditional objective function, i.e., the likelihood of output (response) given input (message) is unsuited to response g...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	47,804
2402.07585	Identifying architectural design decisions for achieving green ML serving	The growing use of large machine learning models highlights concerns about their increasing computational demands. While the energy consumption of their training phase has received attention, fewer works have considered the inference phase. For ML inference, the binding of ML models to the ML system for user access, kn...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	428,771
2308.00692	LISA: Reasoning Segmentation via Large Language Model	Although perception systems have made remarkable advancements in recent years, they still rely on explicit human instruction or pre-defined categories to identify the target objects before executing visual recognition tasks. Such systems cannot actively reason and comprehend implicit user intention. In this work, we pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	383,019
1806.01257	The laws of physics do not prohibit counterfactual communication	It has been conjectured that counterfactual communication is impossible, even for post-selected quantum particles. We strongly challenge this by proposing precisely such a counterfactual scheme where -- unambiguously -- none of Alice's photons that correctly contribute to her information about Bob's message have been t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	99,512
2004.14641	Query-level Early Exit for Additive Learning-to-Rank Ensembles	Search engine ranking pipelines are commonly based on large ensembles of machine-learned decision trees. The tight constraints on query response time recently motivated researchers to investigate algorithms to make faster the traversal of the additive ensemble or to early terminate the evaluation of documents that are ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	174,961
1306.2967	Optimization of Clustering for Clustering-based Image Denoising	In this paper, the problem of de-noising of an image contaminated with additive white Gaussian noise (AWGN) is studied. This subject has been continued to be an open problem in signal processing for more than 50 years. In the present paper, we suggest a method based on global clustering of image constructing blocks. No...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	25,167
0911.1708	Different goals in multiscale simulations and how to reach them	In this paper we sum up our works on multiscale programs, mainly simulations. We first start with describing what multiscaling is about, how it helps perceiving signal from a background noise in a ?ow of data for example, for a direct perception by a user or for a further use by another program. We then give three exam...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	4,904
2107.08142	Autonomy 2.0: Why is self-driving always 5 years away?	Despite the numerous successes of machine learning over the past decade (image recognition, decision-making, NLP, image synthesis), self-driving technology has not yet followed the same trend. In this paper, we study the history, composition, and development bottlenecks of the modern self-driving stack. We argue that t...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	246,629
1808.00661	Adaptive Temporal Encoding Network for Video Instance-level Human Parsing	Beyond the existing single-person and multiple-person human parsing tasks in static images, this paper makes the first attempt to investigate a more realistic video instance-level human parsing that simultaneously segments out each person instance and parses each instance into more fine-grained parts (e.g., head, leg, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,432
2009.09776	Weight Training Analysis of Sportsmen with Kinect Bioinformatics for Form Improvement	Sports franchises invest a lot in training their athletes. use of latest technology for this purpose is also very common. We propose a system of capturing motion of athletes during weight training and analyzing that data to find out any shortcomings and imperfections. Our system uses Kinect depth image to compute diffe...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	196,684
2107.06676	Higgs Boson Classification: Brain-inspired BCPNN Learning with StreamBrain	One of the most promising approaches for data analysis and exploration of large data sets is Machine Learning techniques that are inspired by brain models. Such methods use alternative learning rules potentially more efficiently than established learning rules. In this work, we focus on the potential of brain-inspired ...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	246,163
2202.03896	Speech Emotion Recognition using Self-Supervised Features	Self-supervised pre-trained features have consistently delivered state-of-art results in the field of natural language processing (NLP); however, their merits in the field of speech emotion recognition (SER) still need further investigation. In this paper we introduce a modular End-to- End (E2E) SER system based on an ...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	279,380
2001.10609	A Review on Object Pose Recovery: from 3D Bounding Box Detectors to Full 6D Pose Estimators	Object pose recovery has gained increasing attention in the computer vision field as it has become an important problem in rapidly evolving technological areas related to autonomous driving, robotics, and augmented reality. Existing review-related studies have addressed the problem at visual level in 2D, going through ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	161,858
2411.12586	Infrared-Assisted Single-Stage Framework for Joint Restoration and Fusion of Visible and Infrared Images under Hazy Conditions	Infrared and visible (IR-VIS) image fusion has gained significant attention for its broad application value. However, existing methods often neglect the complementary role of infrared image in restoring visible image features under hazy conditions. To address this, we propose a joint learning framework that utilizes in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,456
2412.18096	Real-world Deployment and Evaluation of PErioperative AI CHatbot (PEACH) -- a Large Language Model Chatbot for Perioperative Medicine	Large Language Models (LLMs) are emerging as powerful tools in healthcare, particularly for complex, domain-specific tasks. This study describes the development and evaluation of the PErioperative AI CHatbot (PEACH), a secure LLM-based system integrated with local perioperative guidelines to support preoperative clinic...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	520,253
2412.20045	Enhancing Diffusion Models for Inverse Problems with Covariance-Aware Posterior Sampling	Inverse problems exist in many disciplines of science and engineering. In computer vision, for example, tasks such as inpainting, deblurring, and super resolution can be effectively modeled as inverse problems. Recently, denoising diffusion probabilistic models (DDPMs) are shown to provide a promising solution to noisy...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	521,073
1610.01563	DeepGaze II: Reading fixations from deep features trained on object recognition	Here we present DeepGaze II, a model that predicts where people look in images. The model uses the features from the VGG-19 deep neural network trained to identify objects in images. Contrary to other saliency models that use deep features, here we use the VGG features for saliency prediction with no additional fine-tu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	61,986
2304.08821	TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models	Data augmentation has been established as an efficacious approach to supplement useful information for low-resource datasets. Traditional augmentation techniques such as noise injection and image transformations have been widely used. In addition, generative data augmentation (GDA) has been shown to produce more divers...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	358,832
2206.11943	TIAger: Tumor-Infiltrating Lymphocyte Scoring in Breast Cancer for the TiGER Challenge	The quantification of tumor-infiltrating lymphocytes (TILs) has been shown to be an independent predictor for prognosis of breast cancer patients. Typically, pathologists give an estimate of the proportion of the stromal region that contains TILs to obtain a TILs score. The Tumor InfiltratinG lymphocytes in breast canc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	304,425

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