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
2206.04739	I'm Me, We're Us, and I'm Us: Tri-directional Contrastive Learning on Hypergraphs	Although machine learning on hypergraphs has attracted considerable attention, most of the works have focused on (semi-)supervised learning, which may cause heavy labeling costs and poor generalization. Recently, contrastive learning has emerged as a successful unsupervised representation learning method. Despite the p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	301,746
2111.06538	Competitive epidemic networks with multiple survival-of-the-fittest outcomes	We use a deterministic model to study two competing viruses spreading over a two-layer network in the Susceptible--Infected--Susceptible (SIS) framework, and address a central problem of identifying the winning virus in a "survival-of-the-fittest" battle. Existing sufficient conditions ensure that the same virus always...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	266,104
2308.07104	FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving	Key-point-based scene understanding is fundamental for autonomous driving applications. At the same time, optical flow plays an important role in many vision tasks. However, due to the implicit bias of equal attention on all points, classic data-driven optical flow estimation methods yield less satisfactory performance...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	385,389
2406.14206	Live Video Captioning	Dense video captioning is the task that involves the detection and description of events within video sequences. While traditional approaches focus on offline solutions where the entire video of analysis is available for the captioning model, in this work we introduce a paradigm shift towards Live Video Captioning (LVC...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	466,204
2008.02352	Efficient Compactions Between Storage Tiers with PrismDB	In recent years, emerging storage hardware technologies have focused on divergent goals: better performance or lower cost-per-bit. Correspondingly, data systems that employ these technologies are typically optimized either to be fast (but expensive) or cheap (but slow). We take a different approach: by architecting a s...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	190,586
2203.09219	Centrality Measures in multi-layer Knowledge Graphs	Knowledge graphs play a central role for linking different data which leads to multiple layers. Thus, they are widely used in big data integration, especially for connecting data from different domains. Few studies have investigated the questions how multiple layers within graphs impact methods and algorithms developed...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	286,081
2004.13912	Neural Additive Models: Interpretable Machine Learning with Neural Nets	Deep neural networks (DNNs) are powerful black-box predictors that have achieved impressive performance on a wide variety of tasks. However, their accuracy comes at the cost of intelligibility: it is usually unclear how they make their decisions. This hinders their applicability to high stakes decision-making domains s...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	174,711
2004.11515	Nonconvex regularization for sparse neural networks	Convex $\ell_1$ regularization using an infinite dictionary of neurons has been suggested for constructing neural networks with desired approximation guarantees, but can be affected by an arbitrary amount of over-parametrization. This can lead to a loss of sparsity and result in networks with too many active neurons fo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	173,933
2307.04684	FreeDrag: Feature Dragging for Reliable Point-based Image Editing	To serve the intricate and varied demands of image editing, precise and flexible manipulation in image content is indispensable. Recently, Drag-based editing methods have gained impressive performance. However, these methods predominantly center on point dragging, resulting in two noteworthy drawbacks, namely "miss tra...	true	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	378,486
1703.03389	Faster Greedy MAP Inference for Determinantal Point Processes	Determinantal point processes (DPPs) are popular probabilistic models that arise in many machine learning tasks, where distributions of diverse sets are characterized by matrix determinants. In this paper, we develop fast algorithms to find the most likely configuration (MAP) of large-scale DPPs, which is NP-hard in ge...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	69,726
2301.08180	The throughput in multi-channel (slotted) ALOHA: large deviations and analysis of bad events	We consider ALOHA and slotted ALOHA protocols as medium access rules for a multi-channel message delivery system. Users decide randomly and independently with a minimal amount of knowledge about the system at random times to make a message emission attempt. We consider the two cases that the system has a fixed number o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	341,130
2007.07228	Disturbance Decoupling for Gradient-based Multi-Agent Learning with Quadratic Costs	Motivated by applications of multi-agent learning in noisy environments, this paper studies the robustness of gradient-based learning dynamics with respect to disturbances. While disturbances injected along a coordinate corresponding to any individual player's actions can always affect the overall learning dynamics, a ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	187,272
2301.13821	Complete Neural Networks for Complete Euclidean Graphs	Neural networks for point clouds, which respect their natural invariance to permutation and rigid motion, have enjoyed recent success in modeling geometric phenomena, from molecular dynamics to recommender systems. Yet, to date, no model with polynomial complexity is known to be complete, that is, able to distinguish b...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,045
2004.05224	Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review	Autonomous vehicles were experiencing rapid development in the past few years. However, achieving full autonomy is not a trivial task, due to the nature of the complex and dynamic driving environment. Therefore, autonomous vehicles are equipped with a suite of different sensors to ensure robust, accurate environmental ...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	172,121
2102.00327	Learning Interaction Kernels for Agent Systems on Riemannian Manifolds	Interacting agent and particle systems are extensively used to model complex phenomena in science and engineering. We consider the problem of learning interaction kernels in these dynamical systems constrained to evolve on Riemannian manifolds from given trajectory data. The models we consider are based on interaction ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	217,745
2002.10348	Low-Resource Knowledge-Grounded Dialogue Generation	Responding with knowledge has been recognized as an important capability for an intelligent conversational agent. Yet knowledge-grounded dialogues, as training data for learning such a response generation model, are difficult to obtain. Motivated by the challenge in practice, we consider knowledge-grounded dialogue gen...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	165,375
2408.07084	Dynamic Hypergraph-Enhanced Prediction of Sequential Medical Visits	This study introduces a pioneering Dynamic Hypergraph Networks (DHCE) model designed to predict future medical diagnoses from electronic health records with enhanced accuracy. The DHCE model innovates by identifying and differentiating acute and chronic diseases within a patient's visit history, constructing dynamic hy...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	480,445
1404.3285	An Integer Programming Model for the Dynamic Location and Relocation of Emergency Vehicles: A Case Study	In this paper, we address the dynamic Emergency Medical Service (EMS) systems. A dynamic location model is presented that tries to locate and relocate the ambulances. The proposed model controls the movements and locations of ambulances in order to provide a better coverage of the demand points under different fluctuat...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	32,286
2306.12251	GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection	With a long history of traditional Graph Anomaly Detection (GAD) algorithms and recently popular Graph Neural Networks (GNNs), it is still not clear (1) how they perform under a standard comprehensive setting, (2) whether GNNs can outperform traditional algorithms such as tree ensembles, and (3) how about their efficie...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	374,884
2412.01300	Event-Based Tracking Any Point with Motion-Augmented Temporal Consistency	Tracking Any Point (TAP) plays a crucial role in motion analysis. Video-based approaches rely on iterative local matching for tracking, but they assume linear motion during the blind time between frames, which leads to target point loss under large displacements or nonlinear motion. The high temporal resolution and mot...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,060
2102.07074	TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up	The recent explosive interest on transformers has suggested their potential to become powerful "universal" models for computer vision tasks, such as classification, detection, and segmentation. While those attempts mainly study the discriminative models, we explore transformers on some more notoriously difficult vision...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	219,979
2306.08487	Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation	Zero-Shot Learning (ZSL), which aims at automatically recognizing unseen objects, is a promising learning paradigm to understand new real-world knowledge for machines continuously. Recently, the Knowledge Graph (KG) has been proven as an effective scheme for handling the zero-shot task with large-scale and non-attribut...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	373,426
2201.08598	Taxonomy Enrichment with Text and Graph Vector Representations	Knowledge graphs such as DBpedia, Freebase or Wikidata always contain a taxonomic backbone that allows the arrangement and structuring of various concepts in accordance with the hypo-hypernym ("class-subclass") relationship. With the rapid growth of lexical resources for specific domains, the problem of automatic exten...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	276,389
2312.13746	Video Recognition in Portrait Mode	The creation of new datasets often presents new challenges for video recognition and can inspire novel ideas while addressing these challenges. While existing datasets mainly comprise landscape mode videos, our paper seeks to introduce portrait mode videos to the research community and highlight the unique challenges a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	417,404
2307.05946	A Bayesian approach to quantifying uncertainties and improving generalizability in traffic prediction models	Deep-learning models for traffic data prediction can have superior performance in modeling complex functions using a multi-layer architecture. However, a major drawback of these approaches is that most of these approaches do not offer forecasts with uncertainty estimates, which are essential for traffic operations and ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	378,916
1504.07442	Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey	Computer Vision, either alone or combined with other technologies such as radar or Lidar, is one of the key technologies used in Advanced Driver Assistance Systems (ADAS). Its role understanding and analysing the driving scene is of great importance as it can be noted by the number of ADAS applications that use this te...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	42,536
2211.03930	ReLoc: A Restoration-Assisted Framework for Robust Image Tampering Localization	With the spread of tampered images, locating the tampered regions in digital images has drawn increasing attention. The existing image tampering localization methods, however, suffer from severe performance degradation when the tampered images are subjected to some post-processing, as the tampering traces would be dist...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	329,079
2205.09592	Transferable Physical Attack against Object Detection with Separable Attention	Transferable adversarial attack is always in the spotlight since deep learning models have been demonstrated to be vulnerable to adversarial samples. However, existing physical attack methods do not pay enough attention on transferability to unseen models, thus leading to the poor performance of black-box attack.In thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	297,331
1501.04537	Coupled Depth Learning	In this paper we propose a method for estimating depth from a single image using a coarse to fine approach. We argue that modeling the fine depth details is easier after a coarse depth map has been computed. We express a global (coarse) depth map of an image as a linear combination of a depth basis learned from trainin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	39,384
2203.00063	Structure from Voltage	Effective resistance (ER) is an attractive way to interrogate the structure of graphs. It is an alternative to computing the eigen-vectors of the graph Laplacian. Graph laplacians are used to find low dimensional structures in high dimensional data. Here too, ER based analysis has advantages over eign-vector based meth...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	282,851
2410.15546	Improved Contact Graph Routing in Delay Tolerant Networks with Capacity and Buffer Constraints	Satellite communications present challenging characteristics. Continuous end-to-end connectivity may not be available due to the large distances between satellites. Moreover, resources such as link capacity and buffer memory may be limited. Routing in satellite networks is therefore both complex and crucial to avoid pa...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	500,595
2103.13342	The Shapley Value of coalition of variables provides better explanations	While Shapley Values (SV) are one of the gold standard for interpreting machine learning models, we show that they are still poorly understood, in particular in the presence of categorical variables or of variables of low importance. For instance, we show that the popular practice that consists in summing the SV of dum...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	226,462
2111.15191	Wideband Beamforming with Rainbow Beam Training using Reconfigurable True-Time-Delay Arrays for Millimeter-Wave Wireless	The decadal research in integrated true-time-delay arrays have seen organic growth enabling realization of wideband beamformers for large arrays with wide aperture widths. This article introduces highly reconfigurable delay elements implementable at analog or digital baseband that enables multiple SSP functions includi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	268,853
1706.01663	Learning Pairwise Disjoint Simple Languages from Positive Examples	A classical problem in grammatical inference is to identify a deterministic finite automaton (DFA) from a set of positive and negative examples. In this paper, we address the related - yet seemingly novel - problem of identifying a set of DFAs from examples that belong to different unknown simple regular languages. We ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	74,843
2102.12413	Designing Explanations for Group Recommender Systems	Explanations are used in recommender systems for various reasons. Users have to be supported in making (high-quality) decisions more quickly. Developers of recommender systems want to convince users to purchase specific items. Users should better understand how the recommender system works and why a specific item has b...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	221,723
2301.02601	SEQUENT: Towards Traceable Quantum Machine Learning using Sequential Quantum Enhanced Training	Applying new computing paradigms like quantum computing to the field of machine learning has recently gained attention. However, as high-dimensional real-world applications are not yet feasible to be solved using purely quantum hardware, hybrid methods using both classical and quantum machine learning paradigms have be...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	339,544
2111.03195	Addressing Multiple Salient Object Detection via Dual-Space Long-Range Dependencies	Salient object detection plays an important role in many downstream tasks. However, complex real-world scenes with varying scales and numbers of salient objects still pose a challenge. In this paper, we directly address the problem of detecting multiple salient objects across complex scenes. We propose a network archit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	265,080
2412.09442	ATPrompt: Textual Prompt Learning with Embedded Attributes	Textual-based prompt learning methods primarily employ multiple learnable soft prompts and hard class tokens in a cascading manner as text prompt inputs, aiming to align image and text (category) spaces for downstream tasks. However, current training is restricted to aligning images with predefined known categories and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,487
1808.05505	Paraphrase Thought: Sentence Embedding Module Imitating Human Language Recognition	Sentence embedding is an important research topic in natural language processing. It is essential to generate a good embedding vector that fully reflects the semantic meaning of a sentence in order to achieve an enhanced performance for various natural language processing tasks, such as machine translation and document...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	105,364
1902.00202	Optimal Attack against Autoregressive Models by Manipulating the Environment	We describe an optimal adversarial attack formulation against autoregressive time series forecast using Linear Quadratic Regulator (LQR). In this threat model, the environment evolves according to a dynamical system; an autoregressive model observes the current environment state and predicts its future values; an attac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	120,357
2406.03287	SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms	Towards energy-efficient artificial intelligence similar to the human brain, the bio-inspired spiking neural networks (SNNs) have advantages of biological plausibility, event-driven sparsity, and binary activation. Recently, large-scale language models exhibit promising generalization capability, making it a valuable i...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	461,182
2409.06520	In Flight Boresight Rectification for Lightweight Airborne Pushbroom Imaging Spectrometry	Hyperspectral cameras have recently been miniaturized for operation on lightweight airborne platforms such as UAV or small aircraft. Unlike frame cameras (RGB or Multispectral), many hyperspectral sensors use a linear array or 'push-broom' scanning design. This design presents significant challenges for image rectifica...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	487,154
2306.14735	Highly engaging events reveal semantic and temporal compression in online community discourse	People nowadays express their opinions in online spaces, using different forms of interactions such as posting, sharing and discussing with one another. How do these digital traces change in response to events happening in the real world? We leverage Reddit conversation data, exploiting its community-based structure, t...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	375,796
2409.03204	Pricing American Options using Machine Learning Algorithms	This study investigates the application of machine learning algorithms, particularly in the context of pricing American options using Monte Carlo simulations. Traditional models, such as the Black-Scholes-Merton framework, often fail to adequately address the complexities of American options, which include the ability ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	485,959
2408.14565	Low-Complexity Coding Techniques for Cloud Radio Access Networks	The problem of coding for the uplink and downlink of cloud radio access networks (C-RAN's) with $K$ users and $L$ relays is considered. It is shown that low-complexity coding schemes that achieve any point in the rate-fronthaul region of joint coding and compression can be constructed starting from at most $4(K+L)-2$ p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	483,590
2411.01898	Best-Arm Identification in Unimodal Bandits	We study the fixed-confidence best-arm identification problem in unimodal bandits, in which the means of the arms increase with the index of the arm up to their maximum, then decrease. We derive two lower bounds on the stopping time of any algorithm. The instance-dependent lower bound suggests that due to the unimodal ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	505,276
2201.11940	Wassersplines for Neural Vector Field--Controlled Animation	Much of computer-generated animation is created by manipulating meshes with rigs. While this approach works well for animating articulated objects like animals, it has limited flexibility for animating less structured free-form objects. We introduce Wassersplines, a novel trajectory inference method for animating unstr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	277,460
2407.08422	On the (In)Security of LLM App Stores	LLM app stores have seen rapid growth, leading to the proliferation of numerous custom LLM apps. However, this expansion raises security concerns. In this study, we propose a three-layer concern framework to identify the potential security risks of LLM apps, i.e., LLM apps with abusive potential, LLM apps with maliciou...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	472,159
2106.03377	On the Skew-Symmetric Binary Sequences and the Merit Factor Problem	The merit factor problem is of practical importance to manifold domains, such as digital communications engineering, radars, system modulation, system testing, information theory, physics, chemistry. However, the merit factor problem is referenced as one of the most difficult optimization problems and it was further co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	239,297
2305.05157	A Generalized Covering Algorithm for Chained Codes	The covering radius is a fundamental property of linear codes that characterizes the trade-off between storage and access in linear data-query protocols. The generalized covering radius was recently defined by Elimelech and Schwartz for applications in joint-recovery of linear data-queries. In this work we extend a kno...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	363,031
1907.04232	Unified Optimal Analysis of the (Stochastic) Gradient Method	In this note we give a simple proof for the convergence of stochastic gradient (SGD) methods on $\mu$-convex functions under a (milder than standard) $L$-smoothness assumption. We show that for carefully chosen stepsizes SGD converges after $T$ iterations as $O\left( LR^2 \exp \bigl[-\frac{\mu}{4L}T\bigr] + \frac{\sigm...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	138,054
2410.05260	DART: A Diffusion-Based Autoregressive Motion Model for Real-Time Text-Driven Motion Control	Text-conditioned human motion generation, which allows for user interaction through natural language, has become increasingly popular. Existing methods typically generate short, isolated motions based on a single input sentence. However, human motions are continuous and can extend over long periods, carrying rich seman...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	495,637
2211.14963	Neural Architecture for Online Ensemble Continual Learning	Continual learning with an increasing number of classes is a challenging task. The difficulty rises when each example is presented exactly once, which requires the model to learn online. Recent methods with classic parameter optimization procedures have been shown to struggle in such setups or have limitations like non...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	333,065
1708.02735	Gaussian Prototypical Networks for Few-Shot Learning on Omniglot	We propose a novel architecture for $k$-shot classification on the Omniglot dataset. Building on prototypical networks, we extend their architecture to what we call Gaussian prototypical networks. Prototypical networks learn a map between images and embedding vectors, and use their clustering for classification. In our...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	78,649
1905.12726	Prioritized Sequence Experience Replay	Experience replay is widely used in deep reinforcement learning algorithms and allows agents to remember and learn from experiences from the past. In an effort to learn more efficiently, researchers proposed prioritized experience replay (PER) which samples important transitions more frequently. In this paper, we propo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	132,855
2003.06965	OmniTact: A Multi-Directional High Resolution Touch Sensor	Incorporating touch as a sensing modality for robots can enable finer and more robust manipulation skills. Existing tactile sensors are either flat, have small sensitive fields or only provide low-resolution signals. In this paper, we introduce OmniTact, a multi-directional high-resolution tactile sensor. OmniTact is d...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	168,280
2407.01219	Searching for Best Practices in Retrieval-Augmented Generation	Retrieval-augmented generation (RAG) techniques have proven to be effective in integrating up-to-date information, mitigating hallucinations, and enhancing response quality, particularly in specialized domains. While many RAG approaches have been proposed to enhance large language models through query-dependent retriev...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	469,195
2006.15772	Multi-sided Exposure Bias in Recommendation	Academic research in recommender systems has been greatly focusing on the accuracy-related measures of recommendations. Even when non-accuracy measures such as popularity bias, diversity, and novelty are studied, it is often solely from the users' perspective. However, many real-world recommenders are often multi-stake...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	184,622
1911.02993	Quantifying Market Efficiency Impacts of Aggregated Distributed Energy Resources	We focus on the aggregation of distributed energy resources (DERs) through a profit-maximizing intermediary that enables participation of DERs in wholesale electricity markets. Particularly, we study the market efficiency brought in by the large-scale deployment of DERs and explore to what extent such benefits are offs...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	152,515
1612.02166	Consensus Based Medical Image Segmentation Using Semi-Supervised Learning And Graph Cuts	Medical image segmentation requires consensus ground truth segmentations to be derived from multiple expert annotations. A novel approach is proposed that obtains consensus segmentations from experts using graph cuts (GC) and semi supervised learning (SSL). Popular approaches use iterative Expectation Maximization (EM)...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	65,196
2411.12676	IoT-Based 3D Pose Estimation and Motion Optimization for Athletes: Application of C3D and OpenPose	This study proposes the IoT-Enhanced Pose Optimization Network (IE-PONet) for high-precision 3D pose estimation and motion optimization of track and field athletes. IE-PONet integrates C3D for spatiotemporal feature extraction, OpenPose for real-time keypoint detection, and Bayesian optimization for hyperparameter tuni...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	509,495
2406.18008	Rate-Distortion-Perception Tradeoff for Gaussian Vector Sources	This paper studies the rate-distortion-perception (RDP) tradeoff for a Gaussian vector source coding problem where the goal is to compress the multi-component source subject to distortion and perception constraints. The purpose of imposing a perception constraint is to ensure visually pleasing reconstructions. This pap...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	467,829
2310.18849	Deep Learning-based Compressed Domain Multimedia for Man and Machine: A Taxonomy and Application to Point Cloud Classification	In the current golden age of multimedia, human visualization is no longer the single main target, with the final consumer often being a machine which performs some processing or computer vision tasks. In both cases, deep learning plays a undamental role in extracting features from the multimedia representation data, us...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	403,731
1306.0404	Iterative Grassmannian Optimization for Robust Image Alignment	Robust high-dimensional data processing has witnessed an exciting development in recent years, as theoretical results have shown that it is possible using convex programming to optimize data fit to a low-rank component plus a sparse outlier component. This problem is also known as Robust PCA, and it has found applicati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	24,959
1809.08427	Pachinko Prediction: A Bayesian method for event prediction from social media data	The combination of large open data sources with machine learning approaches presents a potentially powerful way to predict events such as protest or social unrest. However, accounting for uncertainty in such models, particularly when using diverse, unstructured datasets such as social media, is essential to guarantee t...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	108,505
cs/0703131	Open Access Scientometrics and the UK Research Assessment Exercise	Scientometric predictors of research performance need to be validated by showing that they have a high correlation with the external criterion they are trying to predict. The UK Research Assessment Exercise (RAE), together with the growing movement toward making the full-texts of research articles freely available on t...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	540,265
1711.02781	RubyStar: A Non-Task-Oriented Mixture Model Dialog System	RubyStar is a dialog system designed to create "human-like" conversation by combining different response generation strategies. RubyStar conducts a non-task-oriented conversation on general topics by using an ensemble of rule-based, retrieval-based and generative methods. Topic detection, engagement monitoring, and con...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	84,114
2302.09363	Autocodificadores Variacionales (VAE) Fundamentos Te\'oricos y Aplicaciones	VAEs are probabilistic graphical models based on neural networks that allow the coding of input data in a latent space formed by simpler probability distributions and the reconstruction, based on such latent variables, of the source data. After training, the reconstruction network, called decoder, is capable of generat...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	346,397
2112.06049	Auto-Tag: Tagging-Data-By-Example in Data Lakes	As data lakes become increasingly popular in large enterprises today, there is a growing need to tag or classify data assets (e.g., files and databases) in data lakes with additional metadata (e.g., semantic column-types), as the inferred metadata can enable a range of downstream applications like data governance (e.g....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	271,038
2109.06867	On Decentralized Multi-Transmitter Coded Caching	This paper investigates a setup consisting of multiple transmitters serving multiple cache-enabled clients through a linear network, which covers both wired and wireless transmission situations. We investigate decentralized coded caching scenarios in which there is either no cooperation or limited cooperation between t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	255,305
2106.10574	Coded Faster-than-Nyquist Signaling for Short Packet Communications	Ultra-reliable low-latency communication (URLLC) requires short packets of data transmission. It is known that when the packet length becomes short, the achievable rate is subject to a penalty when compared to the channel capacity. In this paper, we propose to use faster-than-Nyquist (FTN) signaling to compensate for t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	242,070
2404.05249	SAFE-GIL: SAFEty Guided Imitation Learning for Robotic Systems	Behavior cloning (BC) is a widely-used approach in imitation learning, where a robot learns a control policy by observing an expert supervisor. However, the learned policy can make errors and might lead to safety violations, which limits their utility in safety-critical robotics applications. While prior works have tri...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	445,008
2210.04017	Enhance Sample Efficiency and Robustness of End-to-end Urban Autonomous Driving via Semantic Masked World Model	End-to-end autonomous driving provides a feasible way to automatically maximize overall driving system performance by directly mapping the raw pixels from a front-facing camera to control signals. Recent advanced methods construct a latent world model to map the high dimensional observations into compact latent space. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	322,270
2407.16554	Coarse-to-Fine Proposal Refinement Framework for Audio Temporal Forgery Detection and Localization	Recently, a novel form of audio partial forgery has posed challenges to its forensics, requiring advanced countermeasures to detect subtle forgery manipulations within long-duration audio. However, existing countermeasures still serve a classification purpose and fail to perform meaningful analysis of the start and end...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	475,636
1212.1710	The information and its observer: external and internal information processes, information cooperation, and the origin of the observer intellect	The aim is formal principles of origin information and information process creating information observer self-creating information in interactive observations. The interactive phenomenon creates Yes-No actions of information Bits in its information observer. Information emerges from interacting random field of Kolmogor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	20,191
1910.02812	Policies Modulating Trajectory Generators	We propose an architecture for learning complex controllable behaviors by having simple Policies Modulate Trajectory Generators (PMTG), a powerful combination that can provide both memory and prior knowledge to the controller. The result is a flexible architecture that is applicable to a class of problems with periodic...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	148,347
2412.13682	ChinaTravel: A Real-World Benchmark for Language Agents in Chinese Travel Planning	Recent advances in LLMs, particularly in language reasoning and tool integration, have rapidly sparked the real-world development of Language Agents. Among these, travel planning represents a prominent domain, combining academic challenges with practical value due to its complexity and market demand. However, existing ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	518,400
1706.05886	LiDAR point clouds correction acquired from a moving car based on CAN-bus data	In this paper, we investigate the impact of different kind of car trajectories on LiDAR scans. In fact, LiDAR scanning speeds are considerably slower than car speeds introducing distortions. We propose a method to overcome this issue as well as new metrics based on CAN bus data. Our results suggest that the vehicle tra...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	75,592
2411.05549	Streaming Network for Continual Learning of Object Relocations under Household Context Drifts	In most applications, robots need to adapt to new environments and be multi-functional without forgetting previous information. This requirement gains further importance in real-world scenarios where robots operate in coexistence with humans. In these complex environments, human actions inevitably lead to changes, requ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	506,706
2201.10401	Improving Proximity Classification for Contact Tracing using a Multi-channel Approach	Due to the COVID 19 pandemic, smartphone-based proximity tracing systems became of utmost interest. Many of these systems use BLE signals to estimate the distance between two persons. The quality of this method depends on many factors and, therefore, does not always deliver accurate results. In this paper, we present a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	276,981
2307.14568	Evaluation of Safety Constraints in Autonomous Navigation with Deep Reinforcement Learning	While reinforcement learning algorithms have had great success in the field of autonomous navigation, they cannot be straightforwardly applied to the real autonomous systems without considering the safety constraints. The later are crucial to avoid unsafe behaviors of the autonomous vehicle on the road. To highlight th...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	381,973
2204.06251	Experimental Standards for Deep Learning in Natural Language Processing Research	The field of Deep Learning (DL) has undergone explosive growth during the last decade, with a substantial impact on Natural Language Processing (NLP) as well. Yet, compared to more established disciplines, a lack of common experimental standards remains an open challenge to the field at large. Starting from fundamental...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	291,280
2011.00928	Learning in the Wild with Incremental Skeptical Gaussian Processes	The ability to learn from human supervision is fundamental for personal assistants and other interactive applications of AI. Two central challenges for deploying interactive learners in the wild are the unreliable nature of the supervision and the varying complexity of the prediction task. We address a simple but repre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	204,427
2403.08277	VIGFace: Virtual Identity Generation for Privacy-Free Face Recognition	Deep learning-based face recognition continues to face challenges due to its reliance on huge datasets obtained from web crawling, which can be costly to gather and raise significant real-world privacy concerns. To address this issue, we propose VIGFace, a novel framework capable of generating synthetic facial images. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	437,271
2008.10678	Probabilistic Deep Learning for Instance Segmentation	Probabilistic convolutional neural networks, which predict distributions of predictions instead of point estimates, led to recent advances in many areas of computer vision, from image reconstruction to semantic segmentation. Besides state of the art benchmark results, these networks made it possible to quantify local u...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	193,059
2312.07843	Foundation Models in Robotics: Applications, Challenges, and the Future	We survey applications of pretrained foundation models in robotics. Traditional deep learning models in robotics are trained on small datasets tailored for specific tasks, which limits their adaptability across diverse applications. In contrast, foundation models pretrained on internet-scale data appear to have superio...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	415,079
2004.01241	Semantic Segmentation of Underwater Imagery: Dataset and Benchmark	In this paper, we present the first large-scale dataset for semantic Segmentation of Underwater IMagery (SUIM). It contains over 1500 images with pixel annotations for eight object categories: fish (vertebrates), reefs (invertebrates), aquatic plants, wrecks/ruins, human divers, robots, and sea-floor. The images have b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	170,854
1909.01567	A Non-commutative Bilinear Model for Answering Path Queries in Knowledge Graphs	Bilinear diagonal models for knowledge graph embedding (KGE), such as DistMult and ComplEx, balance expressiveness and computational efficiency by representing relations as diagonal matrices. Although they perform well in predicting atomic relations, composite relations (relation paths) cannot be modeled naturally by t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	143,941
2010.12011	CellCycleGAN: Spatiotemporal Microscopy Image Synthesis of Cell Populations using Statistical Shape Models and Conditional GANs	Automatic analysis of spatio-temporal microscopy images is inevitable for state-of-the-art research in the life sciences. Recent developments in deep learning provide powerful tools for automatic analyses of such image data, but heavily depend on the amount and quality of provided training data to perform well. To this...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	202,517
2502.02133	Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification	The fields of MPC and RL consider two successful control techniques for Markov decision processes. Both approaches are derived from similar fundamental principles, and both are widely used in practical applications, including robotics, process control, energy systems, and autonomous driving. Despite their similarities,...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	530,192
2010.04826	On Task-Level Dialogue Composition of Generative Transformer Model	Task-oriented dialogue systems help users accomplish tasks such as booking a movie ticket and ordering food via conversation. Generative models parameterized by a deep neural network are widely used for next turn response generation in such systems. It is natural for users of the system to want to accomplish multiple t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	199,874
1912.11423	Towards Multicellular Biological Deep Neural Nets Based on Transcriptional Regulation	Artificial neurons built on synthetic gene networks have potential applications ranging from complex cellular decision-making to bioreactor regulation. Furthermore, due to the high information throughput of natural systems, it provides an interesting candidate for biologically-based supercomputing and analog simulation...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	158,564
1812.05189	Massively scalable Sinkhorn distances via the Nystr\"om method	The Sinkhorn "distance", a variant of the Wasserstein distance with entropic regularization, is an increasingly popular tool in machine learning and statistical inference. However, the time and memory requirements of standard algorithms for computing this distance grow quadratically with the size of the data, making th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	116,359
2311.14251	Optimal 1-bit Error Exponent for 2-hop Relaying with Binary-Input Channels	In this paper, we study the problem of relaying a single bit over a tandem of binary-input channels, with the goal of attaining the highest possible error exponent in the exponentially decaying error probability. Our previous work gave an exact characterization of the best possible error exponent in various special cas...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	410,043
1001.4072	Hamming Code for Multiple Sources	We consider Slepian-Wolf (SW) coding of multiple sources and extend the packing bound and the notion of perfect code from conventional channel coding to SW coding with more than two sources. We then introduce Hamming Codes for Multiple Sources (HCMSs) as a potential solution of perfect SW coding for arbitrary number of...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	5,492
2210.06872	Dirichlet process mixture models for non-stationary data streams	In recent years, we have seen a handful of work on inference algorithms over non-stationary data streams. Given their flexibility, Bayesian non-parametric models are a good candidate for these scenarios. However, reliable streaming inference under the concept drift phenomenon is still an open problem for these models. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	323,482
1808.07471	Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks	Deeper and wider Convolutional Neural Networks (CNNs) achieve superior performance but bring expensive computation cost. Accelerating such over-parameterized neural network has received increased attention. A typical pruning algorithm is a three-stage pipeline, i.e., training, pruning, and retraining. Prevailing approa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	105,747
2212.06681	The two sides of the Environmental Kuznets Curve: a socio-semantic analysis	Since the 1990s, the Environmental Kuznets Curve (EKC) hypothesis posits an inverted U-shaped relationship between pollutants and economic development. The hypothesis has attracted a lot of research. We provide here a review of more than 2000 articles that have been published on the EKC. We aim at mapping the developme...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	336,185
2401.02361	An Open and Comprehensive Pipeline for Unified Object Grounding and Detection	Grounding-DINO is a state-of-the-art open-set detection model that tackles multiple vision tasks including Open-Vocabulary Detection (OVD), Phrase Grounding (PG), and Referring Expression Comprehension (REC). Its effectiveness has led to its widespread adoption as a mainstream architecture for various downstream applic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	419,685
2408.00139	Multiway Alignment of Political Attitudes	The related concepts of partisan belief systems, issue alignment, and partisan sorting are central to our understanding of politics. These phenomena have been studied using measures of alignment between pairs of topics, or how much individuals' attitudes toward a topic reveal about their attitudes toward another topic....	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	477,718

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