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
2108.12159	Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework	In this paper, we propose an efficient approach for industrial defect detection that is modeled based on anomaly detection using point pattern data. Most recent works use \textit{global features} for feature extraction to summarize image content. However, global features are not robust against lighting and viewpoint ch...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	252,411
1710.05741	A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning	This paper takes a step towards temporal reasoning in a dynamically changing video, not in the pixel space that constitutes its frames, but in a latent space that describes the non-linear dynamics of the objects in its world. We introduce the Kalman variational auto-encoder, a framework for unsupervised learning of seq...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	82,681
1804.07270	Deep Dynamic Boosted Forest	Random forest is widely exploited as an ensemble learning method. In many practical applications, however, there is still a significant challenge to learn from imbalanced data. To alleviate this limitation, we propose a deep dynamic boosted forest (DDBF), a novel ensemble algorithm that incorporates the notion of hard ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	95,494
1906.02402	An Analysis of Emotion Communication Channels in Fan Fiction: Towards Emotional Storytelling	Centrality of emotion for the stories told by humans is underpinned by numerous studies in literature and psychology. The research in automatic storytelling has recently turned towards emotional storytelling, in which characters' emotions play an important role in the plot development. However, these studies mainly use...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	134,042
1909.04812	Proceedings of the AI-HRI Symposium at AAAI-FSS 2019	The past few years have seen rapid progress in the development of service robots. Universities and companies alike have launched major research efforts toward the deployment of ambitious systems designed to aid human operators performing a variety of tasks. These robots are intended to make those who may otherwise need...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	144,905
2501.07088	MathReader : Text-to-Speech for Mathematical Documents	TTS (Text-to-Speech) document reader from Microsoft, Adobe, Apple, and OpenAI have been serviced worldwide. They provide relatively good TTS results for general plain text, but sometimes skip contents or provide unsatisfactory results for mathematical expressions. This is because most modern academic papers are written...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	524,261
1502.00115	Optimized Projection for Sparse Representation Based Classification	Dimensionality reduction (DR) methods have been commonly used as a principled way to understand the high-dimensional data such as facial images. In this paper, we propose a new supervised DR method called Optimized Projection for Sparse Representation based Classification (OP-SRC), which is based on the recent face rec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	39,767
2404.16251	Prompt Leakage effect and defense strategies for multi-turn LLM interactions	Prompt leakage poses a compelling security and privacy threat in LLM applications. Leakage of system prompts may compromise intellectual property, and act as adversarial reconnaissance for an attacker. A systematic evaluation of prompt leakage threats and mitigation strategies is lacking, especially for multi-turn LLM ...	false	false	false	false	true	false	false	false	true	false	false	false	true	false	false	false	false	false	449,410
2309.12235	Distributed Conjugate Gradient Method via Conjugate Direction Tracking	We present a distributed conjugate gradient method for distributed optimization problems, where each agent computes an optimal solution of the problem locally without any central computation or coordination, while communicating with its immediate, one-hop neighbors over a communication network. Each agent updates its l...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	393,709
1811.00464	A latent topic model for mining heterogenous non-randomly missing electronic health records data	Electronic health records (EHR) are rich heterogeneous collection of patient health information, whose broad adoption provides great opportunities for systematic health data mining. However, heterogeneous EHR data types and biased ascertainment impose computational challenges. Here, we present mixEHR, an unsupervised g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,105
1908.04725	Learning elementary structures for 3D shape generation and matching	We propose to represent shapes as the deformation and combination of learnable elementary 3D structures, which are primitives resulting from training over a collection of shape. We demonstrate that the learned elementary 3D structures lead to clear improvements in 3D shape generation and matching. More precisely, we pr...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	141,554
2412.04678	Unsupervised Segmentation by Diffusing, Walking and Cutting	We propose an unsupervised image segmentation method using features from pre-trained text-to-image diffusion models. Inspired by classic spectral clustering approaches, we construct adjacency matrices from self-attention layers between image patches and recursively partition using Normalised Cuts. A key insight is that...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	514,513
2204.04462	A3CLNN: Spatial, Spectral and Multiscale Attention ConvLSTM Neural Network for Multisource Remote Sensing Data Classification	The problem of effectively exploiting the information multiple data sources has become a relevant but challenging research topic in remote sensing. In this paper, we propose a new approach to exploit the complementarity of two data sources: hyperspectral images (HSIs) and light detection and ranging (LiDAR) data. Speci...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	290,667
2410.11870	Post-Userist Recommender Systems : A Manifesto	We define userist recommendation as an approach to recommender systems framed solely in terms of the relation between the user and system. Post-userist recommendation posits a larger field of relations in which stakeholders are embedded and distinguishes the recommendation function (which can potentially connect creato...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	498,758
1804.08087	Anchor-based Nearest Class Mean Loss for Convolutional Neural Networks	Discriminative features are critical for machine learning applications. Most existing deep learning approaches, however, rely on convolutional neural networks (CNNs) for learning features, whose discriminant power is not explicitly enforced. In this paper, we propose a novel approach to train deep CNNs by imposing the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	95,687
2310.13499	DistillCSE: Distilled Contrastive Learning for Sentence Embeddings	This paper proposes the DistillCSE framework, which performs contrastive learning under the self-training paradigm with knowledge distillation. The potential advantage of DistillCSE is its self-enhancing feature: using a base model to provide additional supervision signals, a stronger model may be learned through knowl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	401,468
2009.05792	A CNN Based Approach for the Near-Field Photometric Stereo Problem	Reconstructing the 3D shape of an object using several images under different light sources is a very challenging task, especially when realistic assumptions such as light propagation and attenuation, perspective viewing geometry and specular light reflection are considered. Many of works tackling Photometric Stereo (P...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	195,428
2210.17170	Efficient Document Retrieval by End-to-End Refining and Quantizing BERT Embedding with Contrastive Product Quantization	Efficient document retrieval heavily relies on the technique of semantic hashing, which learns a binary code for every document and employs Hamming distance to evaluate document distances. However, existing semantic hashing methods are mostly established on outdated TFIDF features, which obviously do not contain lots o...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	327,597
1901.04675	EV Charging Optimization based on Day-ahead Pricing Incorporating Consumer Behavior	With the increasing penetration of electric vehicles (EVs) into the automotive market, the electricity peak demand would increase significantly due to home-EV-charging. This paper tackles this problem by defining an 'ideal' EV consumption profile, from which a day-ahead pricing model is derived. Based on historical res...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	118,642
2404.09633	In-Context Translation: Towards Unifying Image Recognition, Processing, and Generation	We propose In-Context Translation (ICT), a general learning framework to unify visual recognition (e.g., semantic segmentation), low-level image processing (e.g., denoising), and conditional image generation (e.g., edge-to-image synthesis). Thanks to unification, ICT significantly reduces the inherent inductive bias th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	446,771
2211.03888	Proceedings of Principle and practice of data and Knowledge Acquisition Workshop 2022 (PKAW 2022)	Over the past two decades, PKAW has provided a forum for researchers and practitioners to discuss the state-of-the-arts in the area of knowledge acquisition and machine intelligence (MI, also Artificial Intelligence, AI). PKAW2022 will continue the above focus and welcome the contributions on the multi-disciplinary app...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	329,064
2404.14027	OccFeat: Self-supervised Occupancy Feature Prediction for Pretraining BEV Segmentation Networks	We introduce a self-supervised pretraining method, called OccFeat, for camera-only Bird's-Eye-View (BEV) segmentation networks. With OccFeat, we pretrain a BEV network via occupancy prediction and feature distillation tasks. Occupancy prediction provides a 3D geometric understanding of the scene to the model. However, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	448,540
2008.12091	Limitations of Implicit Bias in Matrix Sensing: Initialization Rank Matters	In matrix sensing, we first numerically identify the sensitivity to the initialization rank as a new limitation of the implicit bias of gradient flow. We will partially quantify this phenomenon mathematically, where we establish that the gradient flow of the empirical risk is implicitly biased towards low-rank outcomes...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	193,481
2303.15324	Can Large Language Models design a Robot?	Large Language Models can lead researchers in the design of robots.	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	354,451
1911.00954	Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs	In order to make good decision under uncertainty an agent must learn from observations. To do so, two of the most common frameworks are Contextual Bandits and Markov Decision Processes (MDPs). In this paper, we study whether there exist algorithms for the more general framework (MDP) which automatically provide the bes...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	151,967
1601.02284	Update or Wait: How to Keep Your Data Fresh	In this work, we study how to optimally manage the freshness of information updates sent from a source node to a destination via a channel. A proper metric for data freshness at the destination is the age-of-information, or simply age, which is defined as how old the freshest received update is since the moment that th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	50,818
2401.05045	Improved Bounds on the Number of Support Points of the Capacity-Achieving Input for Amplitude Constrained Poisson Channels	This work considers a discrete-time Poisson noise channel with an input amplitude constraint $\mathsf{A}$ and a dark current parameter $\lambda$. It is known that the capacity-achieving distribution for this channel is discrete with finitely many points. Recently, for $\lambda=0$, a lower bound of order $\sqrt{\mathsf{...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	420,630
2203.07285	Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts	Generative commonsense reasoning (GCR) in natural language is to reason about the commonsense while generating coherent text. Recent years have seen a surge of interest in improving the generation quality of commonsense reasoning tasks. Nevertheless, these approaches have seldom investigated diversity in the GCR tasks,...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	285,385
2011.11637	Nudge Attacks on Point-Cloud DNNs	The wide adaption of 3D point-cloud data in safety-critical applications such as autonomous driving makes adversarial samples a real threat. Existing adversarial attacks on point clouds achieve high success rates but modify a large number of points, which is usually difficult to do in real-life scenarios. In this paper...	false	false	false	false	true	false	true	false	false	false	false	true	true	false	false	false	false	false	207,892
2006.16442	Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning	We consider the problem of factorizing a structured 3-way tensor into its constituent Canonical Polyadic (CP) factors. This decomposition, which can be viewed as a generalization of singular value decomposition (SVD) for tensors, reveals how the tensor dimensions (features) interact with each other. However, since the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	184,811
1812.05206	Design Pseudo Ground Truth with Motion Cue for Unsupervised Video Object Segmentation	One major technique debt in video object segmentation is to label the object masks for training instances. As a result, we propose to prepare inexpensive, yet high quality pseudo ground truth corrected with motion cue for video object segmentation training. Our method conducts semantic segmentation using instance segme...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	116,361
1904.09856	Learning to Calibrate Straight Lines for Fisheye Image Rectification	This paper presents a new deep-learning based method to simultaneously calibrate the intrinsic parameters of fisheye lens and rectify the distorted images. Assuming that the distorted lines generated by fisheye projection should be straight after rectification, we propose a novel deep neural network to impose explicit ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	128,501
2102.06228	Learning Gaussian-Bernoulli RBMs using Difference of Convex Functions Optimization	The Gaussian-Bernoulli restricted Boltzmann machine (GB-RBM) is a useful generative model that captures meaningful features from the given $n$-dimensional continuous data. The difficulties associated with learning GB-RBM are reported extensively in earlier studies. They indicate that the training of the GB-RBM using th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,678
2004.14704	A Span-based Linearization for Constituent Trees	We propose a novel linearization of a constituent tree, together with a new locally normalized model. For each split point in a sentence, our model computes the normalizer on all spans ending with that split point, and then predicts a tree span from them. Compared with global models, our model is fast and parallelizabl...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	174,981
2205.02116	Optimizing One-pixel Black-box Adversarial Attacks	The output of Deep Neural Networks (DNN) can be altered by a small perturbation of the input in a black box setting by making multiple calls to the DNN. However, the high computation and time required makes the existing approaches unusable. This work seeks to improve the One-pixel (few-pixel) black-box adversarial atta...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	294,849
1806.07155	Semi-supervised Hashing for Semi-Paired Cross-View Retrieval	Recently, hashing techniques have gained importance in large-scale retrieval tasks because of their retrieval speed. Most of the existing cross-view frameworks assume that data are well paired. However, the fully-paired multiview situation is not universal in real applications. The aim of the method proposed in this pa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	100,854
2207.07483	A Systematic Review and Replicability Study of BERT4Rec for Sequential Recommendation	BERT4Rec is an effective model for sequential recommendation based on the Transformer architecture. In the original publication, BERT4Rec claimed superiority over other available sequential recommendation approaches (e.g. SASRec), and it is now frequently being used as a state-of-the art baseline for sequential recomme...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	308,213
2010.03222	Unsupervised Evaluation for Question Answering with Transformers	It is challenging to automatically evaluate the answer of a QA model at inference time. Although many models provide confidence scores, and simple heuristics can go a long way towards indicating answer correctness, such measures are heavily dataset-dependent and are unlikely to generalize. In this work, we begin by inv...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	199,330
1710.09289	Automated cardiovascular magnetic resonance image analysis with fully convolutional networks	Cardiovascular magnetic resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction and myocardial mass, providing information for diagnosis and monitoring o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	83,184
1203.3477	A Scalable Method for Solving High-Dimensional Continuous POMDPs Using Local Approximation	Partially-Observable Markov Decision Processes (POMDPs) are typically solved by finding an approximate global solution to a corresponding belief-MDP. In this paper, we offer a new planning algorithm for POMDPs with continuous state, action and observation spaces. Since such domains have an inherent notion of locality, ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	14,925
2103.11370	Online Convex Optimization with Continuous Switching Constraint	In many sequential decision making applications, the change of decision would bring an additional cost, such as the wear-and-tear cost associated with changing server status. To control the switching cost, we introduce the problem of online convex optimization with continuous switching constraint, where the goal is to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	225,784
2306.08329	Research on an improved Conformer end-to-end Speech Recognition Model with R-Drop Structure	To address the issue of poor generalization ability in end-to-end speech recognition models within deep learning, this study proposes a new Conformer-based speech recognition model called "Conformer-R" that incorporates the R-drop structure. This model combines the Conformer model, which has shown promising results in ...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	373,377
2110.06416	MMIU: Dataset for Visual Intent Understanding in Multimodal Assistants	In multimodal assistant, where vision is also one of the input modalities, the identification of user intent becomes a challenging task as visual input can influence the outcome. Current digital assistants take spoken input and try to determine the user intent from conversational or device context. So, a dataset, which...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	260,609
2005.06879	Solve Traveling Salesman Problem by Monte Carlo Tree Search and Deep Neural Network	We present a self-learning approach that combines deep reinforcement learning and Monte Carlo tree search to solve the traveling salesman problem. The proposed approach has two advantages. First, it adopts deep reinforcement learning to compute the value functions for decision, which removes the need of hand-crafted fe...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	177,132
1909.00437	Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation	The recently proposed massively multilingual neural machine translation (NMT) system has been shown to be capable of translating over 100 languages to and from English within a single model. Its improved translation performance on low resource languages hints at potential cross-lingual transfer capability for downstrea...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	143,635
2404.09574	Predicting and Analyzing Pedestrian Crossing Behavior at Unsignalized Crossings	Understanding and predicting pedestrian crossing behavior is essential for enhancing automated driving and improving driving safety. Predicting gap selection behavior and the use of zebra crossing enables driving systems to proactively respond and prevent potential conflicts. This task is particularly challenging at un...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	446,742
2408.17157	Optimizing Traversal Queries of Sensor Data Using a Rule-Based Reachability Approach	Link Traversal queries face challenges in completeness and long execution time due to the size of the web. Reachability criteria define completeness by restricting the links followed by engines. However, the number of links to dereference remains the bottleneck of the approach. Web environments often have structures ex...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	484,600
2308.06862	Effect of Choosing Loss Function when Using T-batching for Representation Learning on Dynamic Networks	Representation learning methods have revolutionized machine learning on networks by converting discrete network structures into continuous domains. However, dynamic networks that evolve over time pose new challenges. To address this, dynamic representation learning methods have gained attention, offering benefits like ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	385,296
2102.05210	D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention Mechanism	Coronavirus Disease 2019 (COVID-19) has caused great casualties and becomes almost the most urgent public health events worldwide. Computed tomography (CT) is a significant screening tool for COVID-19 infection, and automated segmentation of lung infection in COVID-19 CT images will greatly assist diagnosis and health ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	219,356
1812.06307	Generative adversarial networks for generation and classification of physical rehabilitation movement episodes	This article proposes a method for mathematical modeling of human movements related to patient exercise episodes performed during physical therapy sessions by using artificial neural networks. The generative adversarial network structure is adopted, whereby a discriminative and a generative model are trained concurrent...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	116,585
1904.02383	Artificial Neural Network Modeling for Path Loss Prediction in Urban Environments	Although various linear log-distance path loss models have been developed, advanced models are requiring to more accurately and flexibly represent the path loss for complex environments such as the urban area. This letter proposes an artificial neural network (ANN) based multi-dimensional regression framework for path ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,417
2104.00426	WakaVT: A Sequential Variational Transformer for Waka Generation	Poetry generation has long been a challenge for artificial intelligence. In the scope of Japanese poetry generation, many researchers have paid attention to Haiku generation, but few have focused on Waka generation. To further explore the creative potential of natural language generation systems in Japanese poetry crea...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	227,997
2305.10736	Counterfactual Debiasing for Generating Factually Consistent Text Summaries	Despite substantial progress in abstractive text summarization to generate fluent and informative texts, the factual inconsistency in the generated summaries remains an important yet challenging problem to be solved. In this paper, we construct causal graphs for abstractive text summarization and identify the intrinsic...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	365,208
1310.4849	On the Bayes-optimality of F-measure maximizers	The F-measure, which has originally been introduced in information retrieval, is nowadays routinely used as a performance metric for problems such as binary classification, multi-label classification, and structured output prediction. Optimizing this measure is a statistically and computationally challenging problem, s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	27,843
1903.06261	Graph Hierarchical Convolutional Recurrent Neural Network (GHCRNN) for Vehicle Condition Prediction	The prediction of urban vehicle flow and speed can greatly facilitate people's travel, and also can provide reasonable advice for the decision-making of relevant government departments. However, due to the spatial, temporal and hierarchy of vehicle flow and many influencing factors such as weather, it is difficult to p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	124,338
2010.05171	fairseq S2T: Fast Speech-to-Text Modeling with fairseq	We introduce fairseq S2T, a fairseq extension for speech-to-text (S2T) modeling tasks such as end-to-end speech recognition and speech-to-text translation. It follows fairseq's careful design for scalability and extensibility. We provide end-to-end workflows from data pre-processing, model training to offline (online) ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	200,015
2404.19015	Simple-RF: Regularizing Sparse Input Radiance Fields with Simpler Solutions	Neural Radiance Fields (NeRF) show impressive performance in photo-realistic free-view rendering of scenes. Recent improvements on the NeRF such as TensoRF and ZipNeRF employ explicit models for faster optimization and rendering, as compared to the NeRF that employs an implicit representation. However, both implicit an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	450,472
2005.02161	LambdaNet: Probabilistic Type Inference using Graph Neural Networks	As gradual typing becomes increasingly popular in languages like Python and TypeScript, there is a growing need to infer type annotations automatically. While type annotations help with tasks like code completion and static error catching, these annotations cannot be fully determined by compilers and are tedious to ann...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	175,793
2305.19049	Space MIMO: Direct Unmodified Handheld to Multi-Satellite Communication	This paper examines the uplink transmission of a single-antenna handsheld user to a cluster of satellites, with a focus on utilizing the inter-satellite links to enable cooperative signal detection. Two cases are studied: one with full CSI and the other with partial CSI between satellites. The two cases are compared in...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	369,355
2401.16519	Extending the kinematic theory of rapid movements with new primitives	The Kinematic Theory of rapid movements, and its associated Sigma-Lognormal, model 2D spatiotemporal trajectories. It is constructed mainly as a temporal overlap of curves between virtual target points. Specifically, it uses an arc and a lognormal as primitives for the representation of the trajectory and velocity, res...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	424,861
1710.08107	Probabilistic Pursuits on Graphs	We consider discrete dynamical systems of "ant-like" agents engaged in a sequence of pursuits on a graph environment. The agents emerge one by one at equal time intervals from a source vertex $s$ and pursue each other by greedily attempting to close the distance to their immediate predecessor, the agent that emerged ju...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	83,038
2311.16446	Centre Stage: Centricity-based Audio-Visual Temporal Action Detection	Previous one-stage action detection approaches have modelled temporal dependencies using only the visual modality. In this paper, we explore different strategies to incorporate the audio modality, using multi-scale cross-attention to fuse the two modalities. We also demonstrate the correlation between the distance from...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	410,887
2203.05178	An Audio-Visual Attention Based Multimodal Network for Fake Talking Face Videos Detection	DeepFake based digital facial forgery is threatening the public media security, especially when lip manipulation has been used in talking face generation, the difficulty of fake video detection is further improved. By only changing lip shape to match the given speech, the facial features of identity is hard to be discr...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	284,732
2404.08582	FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation	In the realm of fashion object detection and segmentation for online shopping images, existing state-of-the-art fashion parsing models encounter limitations, particularly when exposed to non-model-worn apparel and close-up shots. To address these failures, we introduce FashionFail; a new fashion dataset with e-commerce...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	446,300
1705.01861	Action Tubelet Detector for Spatio-Temporal Action Localization	Current state-of-the-art approaches for spatio-temporal action localization rely on detections at the frame level that are then linked or tracked across time. In this paper, we leverage the temporal continuity of videos instead of operating at the frame level. We propose the ACtion Tubelet detector (ACT-detector) that ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	72,894
2208.09169	Cost and efficiency requirements for a successful electricity storage in a highly renewable European energy system	Future highly renewable energy systems might require substantial storage deployment. At the current stage, the technology portfolio of dominant storage options is limited to pumped-hydro storage and Li-Ion batteries. It is uncertain which storage design will be able to compete with these options. Considering Europe as ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	313,612
1710.10248	Tensor network language model	We propose a new statistical model suitable for machine learning of systems with long distance correlations such as natural languages. The model is based on directed acyclic graph decorated by multi-linear tensor maps in the vertices and vector spaces in the edges, called tensor network. Such tensor networks have been ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	83,337
2110.05165	Exchangeability-Aware Sum-Product Networks	Sum-Product Networks (SPNs) are expressive probabilistic models that provide exact, tractable inference. They achieve this efficiency by making use of local independence. On the other hand, mixtures of exchangeable variable models (MEVMs) are a class of tractable probabilistic models that make use of exchangeability of...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	260,186
2411.11044	Efficient Federated Unlearning with Adaptive Differential Privacy Preservation	Federated unlearning (FU) offers a promising solution to effectively address the need to erase the impact of specific clients' data on the global model in federated learning (FL), thereby granting individuals the ``Right to be Forgotten". The most straightforward approach to achieve unlearning is to train the model fro...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	508,898
2205.09191	High-Order Multilinear Discriminant Analysis via Order-$\textit{n}$ Tensor Eigendecomposition	Higher-order data with high dimensionality is of immense importance in many areas of machine learning, computer vision, and video analytics. Multidimensional arrays (commonly referred to as tensors) are used for arranging higher-order data structures while keeping the natural representation of the data samples. In the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	297,180
1603.06121	Buried object detection using handheld WEMI with task-driven extended functions of multiple instances	Many effective supervised discriminative dictionary learning methods have been developed in the literature. However, when training these algorithms, precise ground-truth of the training data is required to provide very accurate point-wise labels. Yet, in many applications, accurate labels are not always feasible. This ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	53,444
2002.10131	Modeling Aggression Propagation on Social Media	Cyberaggression has been studied in various contexts and online social platforms, and modeled on different data using state-of-the-art machine and deep learning algorithms to enable automatic detection and blocking of this behavior. Users can be influenced to act aggressively or even bully others because of elevated to...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	165,301
1608.05470	Dual User Selection for Security Enhancement in Uplink Multiuser Systems	This letter proposes a novel dual user selection scheme for uplink transmission with multiple users, where a jamming user and a served user are jointly selected to improve the secrecy performance. Specifically, the jamming user transmits jamming signal with a certain rate, so that the base station (BS) can decode the j...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	59,980
1702.02223	Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18F-FDG PET/CT images	The present study shows that the performance of CNN is not significantly different from the best classical methods and human doctors for classifying mediastinal lymph node metastasis of NSCLC from PET/CT images. Because CNN does not need tumor segmentation or feature calculation, it is more convenient and more objectiv...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	67,945
2110.11316	CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP	CLIP yielded impressive results on zero-shot transfer learning tasks and is considered as a foundation model like BERT or GPT3. CLIP vision models that have a rich representation are pre-trained using the InfoNCE objective and natural language supervision before they are fine-tuned on particular tasks. Though CLIP exce...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	262,440
2311.17978	AutArch: An AI-assisted workflow for object detection and automated recording in archaeological catalogues	The context of this paper is the creation of large uniform archaeological datasets from heterogeneous published resources, such as find catalogues - with the help of AI and Big Data. The paper is concerned with the challenge of consistent assemblages of archaeological data. We cannot simply combine existing records, as...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	411,512
2112.03103	FastWARC: Optimizing Large-Scale Web Archive Analytics	Web search and other large-scale web data analytics rely on processing archives of web pages stored in a standardized and efficient format. Since its introduction in 2008, the IIPC's Web ARCive (WARC) format has become the standard format for this purpose. As a list of individually compressed records of HTTP requests a...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	270,086
1207.4074	An analytical comparison of coalescent-based multilocus methods: The three-taxon case	Incomplete lineage sorting (ILS) is a common source of gene tree incongruence in multilocus analyses. A large number of methods have been developed to infer species trees in the presence of ILS. Here we provide a mathematical analysis of several coalescent-based methods. Our analysis is performed on a three-taxon speci...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	17,529
2306.17038	Comparison of Single- and Multi- Objective Optimization Quality for Evolutionary Equation Discovery	Evolutionary differential equation discovery proved to be a tool to obtain equations with less a priori assumptions than conventional approaches, such as sparse symbolic regression over the complete possible terms library. The equation discovery field contains two independent directions. The first one is purely mathema...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	376,570
1704.01788	A Survey of Skyline Query Processing	Living in the Information Age allows almost everyone have access to a large amount of information and options to choose from in order to fulfill their needs. In many cases, the amount of information available and the rate of change may hide the optimal and truly desired solution. This reveals the need of a mechanism th...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	71,325
2305.06691	Correcting One Error in Non-Binary Channels with Feedback	In this paper, the problem of correction of a single error in $q$-ary symmetric channel with noiseless feedback is considered. We propose an algorithm to construct codes with feedback inductively. For all prime power $q$ we prove that two instances of feedback are sufficient to transmit over the $q$-ary symmetric chann...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	363,634
2411.11906	$\text{S}^{3}$Mamba: Arbitrary-Scale Super-Resolution via Scaleable State Space Model	Arbitrary scale super-resolution (ASSR) aims to super-resolve low-resolution images to high-resolution images at any scale using a single model, addressing the limitations of traditional super-resolution methods that are restricted to fixed-scale factors (e.g., $\times2$, $\times4$). The advent of Implicit Neural Repre...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,220
2302.07510	Best Arm Identification for Stochastic Rising Bandits	Stochastic Rising Bandits (SRBs) model sequential decision-making problems in which the expected reward of the available options increases every time they are selected. This setting captures a wide range of scenarios in which the available options are learning entities whose performance improves (in expectation) over t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	345,753
1808.07185	Keyphrase Generation with Correlation Constraints	In this paper, we study automatic keyphrase generation. Although conventional approaches to this task show promising results, they neglect correlation among keyphrases, resulting in duplication and coverage issues. To solve these problems, we propose a new sequence-to-sequence architecture for keyphrase generation name...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	105,682
2305.10747	Strong Structural Controllability of Structured Networks with MIMO node systems	The article addresses the problem of strong structural controllability of structured networks with multi-input multi-output (MIMO) node systems. The authors first present necessary and sufficient conditions for strong structural controllability, which involve both algebraic and graph-theoretic aspects. These conditions...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	365,213
2401.09819	PPNet: A Two-Stage Neural Network for End-to-end Path Planning	The classical path planners, such as sampling-based path planners, can provide probabilistic completeness guarantees in the sense that the probability that the planner fails to return a solution if one exists, decays to zero as the number of samples approaches infinity. However, finding a near-optimal feasible solution...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	422,397
1910.14258	Towards a Predictive Patent Analytics and Evaluation Platform	The importance of patents is well recognised across many regions of the world. Many patent mining systems have been proposed, but with limited predictive capabilities. In this demo, we showcase how predictive algorithms leveraging the state-of-the-art machine learning and deep learning techniques can be used to improve...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	151,606
2401.02160	Human-in-the-Loop Policy Optimization for Preference-Based Multi-Objective Reinforcement Learning	Multi-objective reinforcement learning (MORL) aims to find a set of high-performing and diverse policies that address trade-offs between multiple conflicting objectives. However, in practice, decision makers (DMs) often deploy only one or a limited number of trade-off policies. Providing too many diversified trade-off ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	419,627
2208.04268	Label-Free Synthetic Pretraining of Object Detectors	We propose a new approach, Synthetic Optimized Layout with Instance Detection (SOLID), to pretrain object detectors with synthetic images. Our "SOLID" approach consists of two main components: (1) generating synthetic images using a collection of unlabelled 3D models with optimized scene arrangement; (2) pretraining an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	312,051
1610.09077	Integrating Topic Models and Latent Factors for Recommendation	Nowadays, we have large amounts of online items in various web-based applications, which makes it an important task to build effective personalized recommender systems so as to save users' efforts in information seeking. One of the most extensively and successfully used methods for personalized recommendation is the Co...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	62,999
1909.04697	When Single Event Upset Meets Deep Neural Networks: Observations, Explorations, and Remedies	Deep Neural Network has proved its potential in various perception tasks and hence become an appealing option for interpretation and data processing in security sensitive systems. However, security-sensitive systems demand not only high perception performance, but also design robustness under various circumstances. Unl...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	144,867
2502.07579	Single-Step Consistent Diffusion Samplers	Sampling from unnormalized target distributions is a fundamental yet challenging task in machine learning and statistics. Existing sampling algorithms typically require many iterative steps to produce high-quality samples, leading to high computational costs that limit their practicality in time-sensitive or resource-c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	532,669
1705.10887	Efficient, sparse representation of manifold distance matrices for classical scaling	Geodesic distance matrices can reveal shape properties that are largely invariant to non-rigid deformations, and thus are often used to analyze and represent 3-D shapes. However, these matrices grow quadratically with the number of points. Thus for large point sets it is common to use a low-rank approximation to the di...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	74,489
1905.12966	Quantifying consensus of rankings based on q-support patterns	Rankings, representing preferences over a set of candidates, are widely used in many information systems, e.g., group decision making and information retrieval. It is of great importance to evaluate the consensus of the obtained rankings from multiple agents. An overall measure of the consensus degree provides an insig...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	132,955
2010.07410	Six Attributes of Unhealthy Conversation	We present a new dataset of approximately 44000 comments labeled by crowdworkers. Each comment is labelled as either 'healthy' or 'unhealthy', in addition to binary labels for the presence of six potentially 'unhealthy' sub-attributes: (1) hostile; (2) antagonistic, insulting, provocative or trolling; (3) dismissive; (...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	200,798
1807.04040	Learning Singularity Avoidance	With the increase in complexity of robotic systems and the rise in non-expert users, it can be assumed that task constraints are not explicitly known. In tasks where avoiding singularity is critical to its success, this paper provides an approach, especially for non-expert users, for the system to learn the constraints...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	102,654
2001.09678	A Robust Real-Time Computing-based Environment Sensing System for Intelligent Vehicle	For intelligent vehicles, sensing the 3D environment is the first but crucial step. In this paper, we build a real-time advanced driver assistance system based on a low-power mobile platform. The system is a real-time multi-scheme integrated innovation system, which combines stereo matching algorithm with machine learn...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	161,637
2106.00421	OpenBox: A Generalized Black-box Optimization Service	Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, engineering, physics, and experimental design. However, it remains a challenge for users to apply BBO methods to their problems at hand with existing software packages, in terms of applicability, performance, and effic...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	238,117
1206.1492	Ordinary Search Engine Users Carrying Out Complex Search Tasks	Web search engines have become the dominant tools for finding information on the Internet. Due to their popularity, users apply them to a wide range of search needs, from simple look-ups to rather complex information tasks. This paper presents the results of a study to investigate the characteristics of these complex i...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	16,375
2501.19184	A Survey on Class-Agnostic Counting: Advancements from Reference-Based to Open-World Text-Guided Approaches	Visual object counting has recently shifted towards class-agnostic counting (CAC), which addresses the challenge of counting objects across arbitrary categories -- a crucial capability for flexible and generalizable counting systems. Unlike humans, who effortlessly identify and count objects from diverse categories wit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	529,049

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