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
2208.03471	Oversquashing in GNNs through the lens of information contraction and graph expansion	The quality of signal propagation in message-passing graph neural networks (GNNs) strongly influences their expressivity as has been observed in recent works. In particular, for prediction tasks relying on long-range interactions, recursive aggregation of node features can lead to an undesired phenomenon called "oversq...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	311,793
2409.07236	3DGCQA: A Quality Assessment Database for 3D AI-Generated Contents	Although 3D generated content (3DGC) offers advantages in reducing production costs and accelerating design timelines, its quality often falls short when compared to 3D professionally generated content. Common quality issues frequently affect 3DGC, highlighting the importance of timely and effective quality assessment....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	487,436
2009.12604	Graph neural induction of value iteration	Many reinforcement learning tasks can benefit from explicit planning based on an internal model of the environment. Previously, such planning components have been incorporated through a neural network that partially aligns with the computational graph of value iteration. Such network have so far been focused on restric...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	197,478
2104.06510	Robotic needle steering in deformable tissues with extreme learning machines	Control strategies for robotic needle steering in soft tissues must account for complex interactions between the needle and the tissue to achieve accurate needle tip positioning. Recent findings show faster robotic command rate can improve the control stability in realistic scenarios. This study proposes the use of Ext...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	false	false	230,097
1710.06611	On community structure validation in real networks	Community structure is a commonly observed feature of real networks. The term refers to the presence in a network of groups of nodes (communities) that feature high internal connectivity, but are poorly connected between each other. Whereas the issue of community detection has been addressed in several works, the probl...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	82,806
2311.17504	PViT-6D: Overclocking Vision Transformers for 6D Pose Estimation with Confidence-Level Prediction and Pose Tokens	In the current state of 6D pose estimation, top-performing techniques depend on complex intermediate correspondences, specialized architectures, and non-end-to-end algorithms. In contrast, our research reframes the problem as a straightforward regression task by exploring the capabilities of Vision Transformers for dir...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,324
2211.15453	An Alphabet of Leakage Measures	We introduce a family of information leakage measures called maximal $\alpha,\beta$-leakage, parameterized by real numbers $\alpha$ and $\beta$. The measure is formalized via an operational definition involving an adversary guessing an unknown function of the data given the released data. We obtain a simple, computable...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	333,272
2105.14564	Evaluating Resilience of Encrypted Traffic Classification Against Adversarial Evasion Attacks	Machine learning and deep learning algorithms can be used to classify encrypted Internet traffic. Classification of encrypted traffic can become more challenging in the presence of adversarial attacks that target the learning algorithms. In this paper, we focus on investigating the effectiveness of different evasion at...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	237,723
2306.15489	Precursor-of-Anomaly Detection for Irregular Time Series	Anomaly detection is an important field that aims to identify unexpected patterns or data points, and it is closely related to many real-world problems, particularly to applications in finance, manufacturing, cyber security, and so on. While anomaly detection has been studied extensively in various fields, detecting fu...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	376,036
2102.10440	Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models	While probabilistic models are an important tool for studying causality, doing so suffers from the intractability of inference. As a step towards tractable causal models, we consider the problem of learning interventional distributions using sum-product networks (SPNs) that are over-parameterized by gate functions, e.g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	221,094
2404.10769	Finite-dimensional approximations of push-forwards on locally analytic functionals	This paper introduces a novel theoretical framework for investigating analytic maps from finite discrete data. Our approach is to consider the push-forward on the space of locally analytic functionals, instead of directly handling the analytic map itself. We establish a methodology enabling appropriate finite-dimension...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	447,244
2407.04249	FeatureSORT: Essential Features for Effective Tracking	In this work, we introduce a novel tracker designed for online multiple object tracking with a focus on being simple, while being effective. we provide multiple feature modules each of which stands for a particular appearance information. By integrating distinct appearance features, including clothing color, style, and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,489
1803.01575	A Comparative Study of Pairwise Learning Methods based on Kernel Ridge Regression	Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction or network inference problems. During the last decade kernel methods have played a dominant role in pairwise learning. They still obtain a stat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	91,911
cs/0612123	Electronic Laboratory Notebook Assisting Reflectance Spectrometry in Legal Medicine	Reflectance spectrometry is a fast and reliable method for the characterisation of human skin if the spectra are analysed with respect to a physical model describing the optical properties of human skin. For a field study performed at the Institute of Legal Medicine and the Freiburg Materials Research Center of the Uni...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	true	539,993
2305.16043	Ordered and Binary Speaker Embedding	Modern speaker recognition systems represent utterances by embedding vectors. Conventional embedding vectors are dense and non-structural. In this paper, we propose an ordered binary embedding approach that sorts the dimensions of the embedding vector via a nested dropout and converts the sorted vectors to binary codes...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	367,894
1712.01572	Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces	Transfer operators such as the Perron--Frobenius or Koopman operator play an important role in the global analysis of complex dynamical systems. The eigenfunctions of these operators can be used to detect metastable sets, to project the dynamics onto the dominant slow processes, or to separate superimposed signals. We ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	86,124
1704.02128	Modeling and Analysis of HetNets with mm-Wave Multi-RAT Small Cells Deployed Along Roads	We characterize a multi tier network with classical macro cells, and multi radio access technology (RAT) small cells, which are able to operate in microwave and millimeter-wave (mm-wave) bands. The small cells are assumed to be deployed along roads modeled as a Poisson line process. This characterization is more realis...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	71,386
2305.13607	Not All Image Regions Matter: Masked Vector Quantization for Autoregressive Image Generation	Existing autoregressive models follow the two-stage generation paradigm that first learns a codebook in the latent space for image reconstruction and then completes the image generation autoregressively based on the learned codebook. However, existing codebook learning simply models all local region information of imag...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	366,577
1807.09574	Redundancy Coefficient Gradual Up-weighting-based Mutual Information Feature Selection Technique for Crypto-ransomware Early Detection	Crypto-ransomware is characterized by its irreversible effect even after the detection and removal. As such, the early detection is crucial to protect user data and files of being held to ransom. Several solutions have proposed utilizing the data extracted during the initial phases of the attacks before the encryption ...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	103,751
2010.04425	WHO 2016 subtyping and automated segmentation of glioma using multi-task deep learning	Accurate characterization of glioma is crucial for clinical decision making. A delineation of the tumor is also desirable in the initial decision stages but is a time-consuming task. Leveraging the latest GPU capabilities, we developed a single multi-task convolutional neural network that uses the full 3D, structural, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	199,737
1206.0111	OpenGM: A C++ Library for Discrete Graphical Models	OpenGM is a C++ template library for defining discrete graphical models and performing inference on these models, using a wide range of state-of-the-art algorithms. No restrictions are imposed on the factor graph to allow for higher-order factors and arbitrary neighborhood structures. Large models with repetitive struc...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	16,279
1811.08047	Optimizing System Quality of Service through Rejuvenation for Long-Running Applications with Real-Time Constraints	Reliability, longevity, availability, and deadline guarantees are the four most important metrics to measure the QoS of long-running safety-critical real-time applications. Software aging is one of the major factors that impact the safety of long-running real-time applications as the degraded performance and increased ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	113,936
2006.08539	Deep Layer-wise Networks Have Closed-Form Weights	There is currently a debate within the neuroscience community over the likelihood of the brain performing backpropagation (BP). To better mimic the brain, training a network $\textit{one layer at a time}$ with only a "single forward pass" has been proposed as an alternative to bypass BP; we refer to these networks as "...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,220
2207.05836	Contextual Bandits with Large Action Spaces: Made Practical	A central problem in sequential decision making is to develop algorithms that are practical and computationally efficient, yet support the use of flexible, general-purpose models. Focusing on the contextual bandit problem, recent progress provides provably efficient algorithms with strong empirical performance when the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	307,680
2501.08086	NOMTO: Neural Operator-based symbolic Model approximaTion and discOvery	While many physical and engineering processes are most effectively described by non-linear symbolic models, existing non-linear symbolic regression (SR) methods are restricted to a limited set of continuous algebraic functions, thereby limiting their applicability to discover higher order non-linear differential relati...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	524,624
1803.06602	Two new classes of quantum MDS codes	Let $p$ be a prime and let $q$ be a power of $p$. In this paper, by using generalized Reed-Solomon (GRS for short) codes and extended GRS codes, we construct two new classes of quantum maximum-distance- separable (MDS) codes with parameters \[ [[tq, tq-2d+2, d]]_{q} \] for any $1 \leq t \leq q, 2 \leq d \leq \lfloor \f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	92,876
2202.09036	Adaptive Experimentation in the Presence of Exogenous Nonstationary Variation	We investigate experiments that are designed to select a treatment arm for population deployment. Multi-armed bandit algorithms can enhance efficiency by dynamically allocating measurement effort towards higher performing arms based on observed feedback. However, such dynamics can result in brittle behavior in the face...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	281,075
2011.01819	Learning Representations from Audio-Visual Spatial Alignment	We introduce a novel self-supervised pretext task for learning representations from audio-visual content. Prior work on audio-visual representation learning leverages correspondences at the video level. Approaches based on audio-visual correspondence (AVC) predict whether audio and video clips originate from the same o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	204,720
2409.15905	Boosting Code-Switching ASR with Mixture of Experts Enhanced Speech-Conditioned LLM	In this paper, we introduce a speech-conditioned Large Language Model (LLM) integrated with a Mixture of Experts (MoE) based connector to address the challenge of Code-Switching (CS) in Automatic Speech Recognition (ASR). Specifically, we propose an Insertion and Deletion of Interruption Token (IDIT) mechanism for bett...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	491,121
2112.12641	Prolog-based agnostic explanation module for structured pattern classification	This paper presents a Prolog-based reasoning module to generate counterfactual explanations given the predictions computed by a black-box classifier. The proposed symbolic reasoning module can also resolve what-if queries using the ground-truth labels instead of the predicted ones. Overall, our approach comprises four ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,022
2112.15530	Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning	Web-based interactions can be frequently represented by an attributed graph, and node clustering in such graphs has received much attention lately. Multiple efforts have successfully applied Graph Convolutional Networks (GCN), though with some limits on accuracy as GCNs have been shown to suffer from over-smoothing iss...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,813
2203.00452	Long-Tailed Classification with Gradual Balanced Loss and Adaptive Feature Generation	The real-world data distribution is essentially long-tailed, which poses great challenge to the deep model. In this work, we propose a new method, Gradual Balanced Loss and Adaptive Feature Generator (GLAG) to alleviate imbalance. GLAG first learns a balanced and robust feature model with Gradual Balanced Loss, then fi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	283,006
2011.10741	A Trace-restricted Kronecker-Factored Approximation to Natural Gradient	Second-order optimization methods have the ability to accelerate convergence by modifying the gradient through the curvature matrix. There have been many attempts to use second-order optimization methods for training deep neural networks. Inspired by diagonal approximations and factored approximations such as Kronecker...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	207,609
2105.03598	Pure Exploration Bandit Problem with General Reward Functions Depending on Full Distributions	In this paper, we study the pure exploration bandit model on general distribution functions, which means that the reward function of each arm depends on the whole distribution, not only its mean. We adapt the racing framework and LUCB framework to solve this problem, and design algorithms for estimating the value of th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	234,196
2009.02119	Speech Gesture Generation from the Trimodal Context of Text, Audio, and Speaker Identity	For human-like agents, including virtual avatars and social robots, making proper gestures while speaking is crucial in human--agent interaction. Co-speech gestures enhance interaction experiences and make the agents look alive. However, it is difficult to generate human-like gestures due to the lack of understanding o...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	194,472
2309.03100	FArMARe: a Furniture-Aware Multi-task methodology for Recommending Apartments based on the user interests	Nowadays, many people frequently have to search for new accommodation options. Searching for a suitable apartment is a time-consuming process, especially because visiting them is often mandatory to assess the truthfulness of the advertisements found on the Web. While this process could be alleviated by visiting the apa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	390,270
2209.11379	Do Current Multi-Task Optimization Methods in Deep Learning Even Help?	Recent research has proposed a series of specialized optimization algorithms for deep multi-task models. It is often claimed that these multi-task optimization (MTO) methods yield solutions that are superior to the ones found by simply optimizing a weighted average of the task losses. In this paper, we perform large-sc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	319,165
1109.2156	Approximate Policy Iteration with a Policy Language Bias: Solving Relational Markov Decision Processes	We study an approach to policy selection for large relational Markov Decision Processes (MDPs). We consider a variant of approximate policy iteration (API) that replaces the usual value-function learning step with a learning step in policy space. This is advantageous in domains where good policies are easier to represe...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	12,100
1901.10615	Data Consistency in Transactional Storage Systems: a Centralised Approach	We introduce an interleaving operational semantics for describing the client-observable behaviour of atomic transactions on distributed key-value stores. Our semantics builds on abstract states comprising centralised, global key-value stores and partial client views. We provide operational definitions of consistency mo...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	120,062
2212.02886	GAS-NeXt: Few-Shot Cross-Lingual Font Generator	Generating new fonts is a time-consuming and labor-intensive task, especially in a language with a huge amount of characters like Chinese. Various deep learning models have demonstrated the ability to efficiently generate new fonts with a few reference characters of that style, but few models support cross-lingual font...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	334,923
2404.00686	Utilizing Maximum Mean Discrepancy Barycenter for Propagating the Uncertainty of Value Functions in Reinforcement Learning	Accounting for the uncertainty of value functions boosts exploration in Reinforcement Learning (RL). Our work introduces Maximum Mean Discrepancy Q-Learning (MMD-QL) to improve Wasserstein Q-Learning (WQL) for uncertainty propagation during Temporal Difference (TD) updates. MMD-QL uses the MMD barycenter for this purpo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	443,066
cmp-lg/9408013	Training and Scaling Preference Functions for Disambiguation	We present an automatic method for weighting the contributions of preference functions used in disambiguation. Initial scaling factors are derived as the solution to a least-squares minimization problem, and improvements are then made by hill-climbing. The method is applied to disambiguating sentences in the ATIS (Air ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,162
2409.00347	Chatting Up Attachment: Using LLMs to Predict Adult Bonds	Obtaining data in the medical field is challenging, making the adoption of AI technology within the space slow and high-risk. We evaluate whether we can overcome this obstacle with synthetic data generated by large language models (LLMs). In particular, we use GPT-4 and Claude 3 Opus to create agents that simulate adul...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	484,895
1912.04549	Expansion of Cyber Attack Data From Unbalanced Datasets Using Generative Techniques	Machine learning techniques help to understand patterns of a dataset to create a defense mechanism against cyber attacks. However, it is difficult to construct a theoretical model due to the imbalances in the dataset for discriminating attacks from the overall dataset. Multilayer Perceptron (MLP) technique will provide...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	156,877
2210.11747	A Finite Blocklength Approach for Wireless Hierarchical Federated Learning in the Presence of Physical Layer Security	In this paper, the wireless hierarchical federated learning (HFL) is revisited by considering physical layer security (PLS). First, we establish a framework for this new problem. Then, we propose a practical finite blocklength (FBL) coding scheme for the wireless HFL in the presence of PLS, which is self-secure when th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	325,437
2501.04561	OpenOmni: Large Language Models Pivot Zero-shot Omnimodal Alignment across Language with Real-time Self-Aware Emotional Speech Synthesis	Recent advancements in omnimodal learning have been achieved in understanding and generation across images, text, and speech, though mainly within proprietary models. Limited omnimodal datasets and the inherent challenges associated with real-time emotional speech generation have hindered open-source progress. To addre...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	523,260
2309.07422	Grid-Aware On-Route Fast-Charging Infrastructure Planning for Battery Electric Bus with Equity Considerations: A Case Study in South King County	The transition from traditional bus fleets to zero-emission ones necessitates the development of effective planning models for battery electric bus (BEB) charging infrastructure. On-route fast charging stations, distinct from on-base charging stations, present unique challenges related to safe operation and power suppl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	391,775
2112.05131	Plenoxels: Radiance Fields without Neural Networks	We introduce Plenoxels (plenoptic voxels), a system for photorealistic view synthesis. Plenoxels represent a scene as a sparse 3D grid with spherical harmonics. This representation can be optimized from calibrated images via gradient methods and regularization without any neural components. On standard, benchmark tasks...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	270,741
2409.18405	Word2Wave: Language Driven Mission Programming for Efficient Subsea Deployments of Marine Robots	This paper explores the design and development of a language-based interface for dynamic mission programming of autonomous underwater vehicles (AUVs). The proposed 'Word2Wave' (W2W) framework enables interactive programming and parameter configuration of AUVs for remote subsea missions. The W2W framework includes: (i) ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	492,239
1812.10961	A Precedent Approach to Assigning Access Rights	To design a discretionary access control policy, a technique is proposed that uses the principle of analogies and is based on both the properties of objects and the properties of subjects. As attributes characterizing these properties, the values of the security attributes of subjects and objects are chosen. The concep...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	true	117,473
2112.00174	Adaptive Optimization with Examplewise Gradients	We propose a new, more general approach to the design of stochastic gradient-based optimization methods for machine learning. In this new framework, optimizers assume access to a batch of gradient estimates per iteration, rather than a single estimate. This better reflects the information that is actually available in ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	269,045
2006.07657	Top influencers can be identified universally by combining classical centralities	Information flow, opinion, and epidemics spread over structured networks. When using individual node centrality indicators to predict which nodes will be among the top influencers or spreaders in a large network, no single centrality has consistently good ranking power. We show that statistical classifiers using two or...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,890
1604.04848	Epipolar Geometry Based On Line Similarity	It is known that epipolar geometry can be computed from three epipolar line correspondences but this computation is rarely used in practice since there are no simple methods to find corresponding lines. Instead, methods for finding corresponding points are widely used. This paper proposes a similarity measure between l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,722
2212.10829	Perching on Moving Inclined Surfaces using Uncertainty Tolerant Planner and Thrust Regulation	Quadrotors with the ability to perch on moving inclined surfaces can save energy and extend their travel distance by leveraging ground vehicles. Achieving dynamic perching places high demands on the performance of trajectory planning and terminal state accuracy in SE(3). However, in the perching process, uncertainties ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	337,629
1710.01142	Finding phonemes: improving machine lip-reading	In machine lip-reading there is continued debate and research around the correct classes to be used for recognition. In this paper we use a structured approach for devising speaker-dependent viseme classes, which enables the creation of a set of phoneme-to-viseme maps where each has a different quantity of visemes rang...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	81,972
2211.04063	Sensing-aided Uplink Channel Estimation for Joint Communication and Sensing	The joint communication and sensing (JCAS) technique has drawn great attention due to its high spectrum efficiency by using the same transmit signal for both communication and sensing. Exploiting the correlation between the uplink (UL) channel and the sensing results, we propose a sensing-aided Kalman filter (SAKF)-bas...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	329,125
2111.04158	A Word on Machine Ethics: A Response to Jiang et al. (2021)	Ethics is one of the longest standing intellectual endeavors of humanity. In recent years, the fields of AI and NLP have attempted to wrangle with how learning systems that interact with humans should be constrained to behave ethically. One proposal in this vein is the construction of morality models that can take in a...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	265,406
2407.11685	Deconvolution with a Box	Deconvolution with a box (square wave) is a key operation for super-resolution with pixel-shift cameras. In general convolution with a box is not invertible. However, we can obtain perfect reconstructions of sparse signals using convex optimization. We give a direct proof that improves on the reconstruction bound that ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	473,573
2411.16758	Bundle Adjusted Gaussian Avatars Deblurring	The development of 3D human avatars from multi-view videos represents a significant yet challenging task in the field. Recent advancements, including 3D Gaussian Splattings (3DGS), have markedly progressed this domain. Nonetheless, existing techniques necessitate the use of high-quality sharp images, which are often im...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	511,162
2010.00494	Mini-DDSM: Mammography-based Automatic Age Estimation	Age estimation has attracted attention for its various medical applications. There are many studies on human age estimation from biomedical images. However, there is no research done on mammograms for age estimation, as far as we know. The purpose of this study is to devise an AI-based model for estimating age from mam...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	198,303
2403.18938	Reshaping Free-Text Radiology Notes Into Structured Reports With Generative Transformers	BACKGROUND: Radiology reports are typically written in a free-text format, making clinical information difficult to extract and use. Recently the adoption of structured reporting (SR) has been recommended by various medical societies thanks to the advantages it offers, e.g. standardization, completeness and information...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	442,136
1801.03233	Eliciting Worker Preference for Task Completion	Current crowdsourcing platforms provide little support for worker feedback. Workers are sometimes invited to post free text describing their experience and preferences in completing tasks. They can also use forums such as Turker Nation1 to exchange preferences on tasks and requesters. In fact, crowdsourcing platforms r...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	88,059
2308.14189	Topology and dynamics of higher-order multiplex networks	Higher-order networks are gaining significant scientific attention due to their ability to encode the many-body interactions present in complex systems. However, higher-order networks have the limitation that they only capture many-body interactions of the same type. To address this limitation, we present a mathematica...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	388,227
2501.12116	Efficient PINNs: Multi-Head Unimodular Regularization of the Solutions Space	We present a machine learning framework to facilitate the solution of nonlinear multiscale differential equations and, especially, inverse problems using Physics-Informed Neural Networks (PINNs). This framework is based on what is called multihead (MH) training, which involves training the network to learn a general sp...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	526,169
2402.12948	GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick	Large language models (LLMs) excellently generate human-like text, but also raise concerns about misuse in fake news and academic dishonesty. Decoding-based watermark, particularly the GumbelMax-trick-based watermark(GM watermark), is a standout solution for safeguarding machine-generated texts due to its notable detec...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	431,058
1903.03418	The meta-problem and the transfer of knowledge between theories of consciousness: a software engineer's take	This contribution examines two radically different explanations of our phenomenal intuitions, one reductive and one strongly non-reductive, and identifies two germane ideas that could benefit many other theories of consciousness. Firstly, the ability of sophisticated agent architectures with a purely physical implement...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	123,728
1810.01344	Unsupervised Emergence of Spatial Structure from Sensorimotor Prediction	Despite its omnipresence in robotics application, the nature of spatial knowledge and the mechanisms that underlie its emergence in autonomous agents are still poorly understood. Recent theoretical work suggests that the concept of space can be grounded by capturing invariants induced by the structure of space in an ag...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,373
2008.01221	Configuration Learning in Underwater Optical Links	A new research problem named configuration learning is described in this work. A novel algorithm is proposed to address the configuration learning problem. The configuration learning problem is defined to be the optimization of the Machine Learning (ML) classifier to maximize the ML performance metric optimizing the tr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	190,246
2406.10254	Towards Signal Processing In Large Language Models	This paper introduces the idea of applying signal processing inside a Large Language Model (LLM). With the recent explosion of generative AI, our work can help bridge two fields together, namely the field of signal processing and large language models. We draw parallels between classical Fourier-Transforms and Fourier ...	false	false	true	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	464,310
2203.08216	Interactive Portrait Harmonization	Current image harmonization methods consider the entire background as the guidance for harmonization. However, this may limit the capability for user to choose any specific object/person in the background to guide the harmonization. To enable flexible interaction between user and harmonization, we introduce interactive...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,713
2204.12834	Power Bundle Adjustment for Large-Scale 3D Reconstruction	We introduce Power Bundle Adjustment as an expansion type algorithm for solving large-scale bundle adjustment problems. It is based on the power series expansion of the inverse Schur complement and constitutes a new family of solvers that we call inverse expansion methods. We theoretically justify the use of power seri...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,624
2210.10464	On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness	Generalization in Reinforcement Learning (RL) aims to learn an agent during training that generalizes to the target environment. This paper studies RL generalization from a theoretical aspect: how much can we expect pre-training over training environments to be helpful? When the interaction with the target environment ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	324,934
2502.03817	Knowing When to Stop Matters: A Unified Algorithm for Online Conversion under Horizon Uncertainty	This paper investigates the online conversion problem, which involves sequentially trading a divisible resource (e.g., energy) under dynamically changing prices to maximize profit. A key challenge in online conversion is managing decisions under horizon uncertainty, where the duration of trading is either known, reveal...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	530,875
2311.16214	DGR: Tackling Drifted and Correlated Noise in Quantum Error Correction via Decoding Graph Re-weighting	Quantum hardware suffers from high error rates and noise, which makes directly running applications on them ineffective. Quantum Error Correction (QEC) is a critical technique towards fault tolerance which encodes the quantum information distributively in multiple data qubits and uses syndrome qubits to check parity. M...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	410,834
1901.00534	Linear colour segmentation revisited	In this work we discuss the known algorithms for linear colour segmentation based on a physical approach and propose a new modification of segmentation algorithm. This algorithm is based on a region adjacency graph framework without a pre-segmentation stage. Proposed edge weight functions are defined from linear image ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	117,797
1811.08632	A Deep Tree-Structured Fusion Model for Single Image Deraining	We propose a simple yet effective deep tree-structured fusion model based on feature aggregation for the deraining problem. We argue that by effectively aggregating features, a relatively simple network can still handle tough image deraining problems well. First, to capture the spatial structure of rain we use dilated ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	114,091
1410.3097	Content and Network Dynamics Behind Egyptian Political Polarization on Twitter	There is little doubt about whether social networks play a role in modern protests. This agreement has triggered an entire research avenue, in which social structure and content analysis have been central --but are typically exploited separately. Here, we combine these two approaches to shed light on the opinion evol...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	36,683
2012.06522	Online Coresets for Clustering with Bregman Divergences	We present algorithms that create coresets in an online setting for clustering problems according to a wide subset of Bregman divergences. Notably, our coresets have a small additive error, similar in magnitude to the lightweight coresets Bachem et. al. 2018, and take update time $O(d)$ for every incoming point where $...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	211,144
2105.10799	Sockpuppet Detection: a Telegram case study	In Online Social Networks (OSN) numerous are the cases in which users create multiple accounts that publicly seem to belong to different people but are actually fake identities of the same person. These fictitious characters can be exploited to carry out abusive behaviors such as manipulating opinions, spreading fake n...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	236,500
2401.07578	Confounded Budgeted Causal Bandits	We study the problem of learning 'good' interventions in a stochastic environment modeled by its underlying causal graph. Good interventions refer to interventions that maximize rewards. Specifically, we consider the setting of a pre-specified budget constraint, where interventions can have non-uniform costs. We show t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	421,594
2410.01806	Samba: Synchronized Set-of-Sequences Modeling for Multiple Object Tracking	Multiple object tracking in complex scenarios - such as coordinated dance performances, team sports, or dynamic animal groups - presents unique challenges. In these settings, objects frequently move in coordinated patterns, occlude each other, and exhibit long-term dependencies in their trajectories. However, it remain...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	493,960
1806.09751	A Practical Incremental Learning Framework For Sparse Entity Extraction	This work addresses challenges arising from extracting entities from textual data, including the high cost of data annotation, model accuracy, selecting appropriate evaluation criteria, and the overall quality of annotation. We present a framework that integrates Entity Set Expansion (ESE) and Active Learning (AL) to r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	101,407
2105.12684	Low Resolution Information Also Matters: Learning Multi-Resolution Representations for Person Re-Identification	As a prevailing task in video surveillance and forensics field, person re-identification (re-ID) aims to match person images captured from non-overlapped cameras. In unconstrained scenarios, person images often suffer from the resolution mismatch problem, i.e., \emph{Cross-Resolution Person Re-ID}. To overcome this pro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	237,068
1712.05110	Optimality Of Community Structure In Complex Networks	Community detection is one of the pivotal tools for discovering the structure of complex networks. Majority of community detection methods rely on optimization of certain quality functions characterizing the proposed community structure. Perhaps, the most commonly used of those quality functions is modularity. Many heu...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	86,694
2003.12506	Hybrid Models for Open Set Recognition	Open set recognition requires a classifier to detect samples not belonging to any of the classes in its training set. Existing methods fit a probability distribution to the training samples on their embedding space and detect outliers according to this distribution. The embedding space is often obtained from a discrimi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	169,934
1812.07608	Differential Evolution with Better and Nearest Option for Function Optimization	Differential evolution(DE) is a conventional algorithm with fast convergence speed. However, DE may be trapped in local optimal solution easily. Many researchers devote themselves to improving DE. In our previously work, whale swarm algorithm have shown its strong searching performance due to its niching based mutation...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	116,841
2209.02984	Semantic Interactive Learning for Text Classification: A Constructive Approach for Contextual Interactions	Interactive Machine Learning (IML) shall enable intelligent systems to interactively learn from their end-users, and is quickly becoming more and more important. Although it puts the human in the loop, interactions are mostly performed via mutual explanations that miss contextual information. Furthermore, current model...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	316,363
2411.09953	Brain-inspired Action Generation with Spiking Transformer Diffusion Policy Model	Spiking Neural Networks (SNNs) has the ability to extract spatio-temporal features due to their spiking sequence. While previous research has primarily foucus on the classification of image and reinforcement learning. In our paper, we put forward novel diffusion policy model based on Spiking Transformer Neural Networks...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	508,433
2205.04297	Learning A Simulation-based Visual Policy for Real-world Peg In Unseen Holes	This paper proposes a learning-based visual peg-in-hole that enables training with several shapes in simulation, and adapting to arbitrary unseen shapes in real world with minimal sim-to-real cost. The core idea is to decouple the generalization of the sensory-motor policy to the design of a fast-adaptable perception m...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	295,599
2103.05577	Parametrized quantum policies for reinforcement learning	With the advent of real-world quantum computing, the idea that parametrized quantum computations can be used as hypothesis families in a quantum-classical machine learning system is gaining increasing traction. Such hybrid systems have already shown the potential to tackle real-world tasks in supervised and generative ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	224,021
2004.05619	Relations among Open-loop Control Ability, Control Strategy Space and Closed-loop Performance for Linear Discrte-time Systems	In this article, the definition on the control ability, and the relation between the open-loop control ability and the closed-loop performance are studied systematically for the linear dynamical systems. Firstly, to define and compare rationally the state control ability between the different controlled plants or one c...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	172,257
2310.18477	Understanding and Improving Ensemble Adversarial Defense	The strategy of ensemble has become popular in adversarial defense, which trains multiple base classifiers to defend against adversarial attacks in a cooperative manner. Despite the empirical success, theoretical explanations on why an ensemble of adversarially trained classifiers is more robust than single ones remain...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	403,561
2401.12375	Development of an NLP-driven computer-based test guide for visually impaired students	In recent years, advancements in Natural Language Processing (NLP) techniques have revolutionized the field of accessibility and exclusivity of testing, particularly for visually impaired students (VIS). CBT has shown in years back its relevance in terms of administering exams electronically, making the test process ea...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	423,350
2410.07040	The Euler-Lagrange equation and optimal control: Preliminary results	Algebraically speaking, linear time-invariant (LTI) systems can be considered as modules. In this framework, controllability is translated as the freeness of the system module. Optimal control mainly relies on quadratic Lagrangians and the consideration of any basis of the system module leads to an open-loop control st...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	496,440
2203.13648	On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks	This paper empirically studies commonly observed training difficulties of Physics-Informed Neural Networks (PINNs) on dynamical systems. Our results indicate that fixed points which are inherent to these systems play a key role in the optimization of the in PINNs embedded physics loss function. We observe that the loss...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	287,710
2404.05624	LTNER: Large Language Model Tagging for Named Entity Recognition with Contextualized Entity Marking	The use of LLMs for natural language processing has become a popular trend in the past two years, driven by their formidable capacity for context comprehension and learning, which has inspired a wave of research from academics and industry professionals. However, for certain NLP tasks, such as NER, the performance of L...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	445,150
2408.01988	MetaWearS: A Shortcut in Wearable Systems Lifecycle with Only a Few Shots	Wearable systems provide continuous health monitoring and can lead to early detection of potential health issues. However, the lifecycle of wearable systems faces several challenges. First, effective model training for new wearable devices requires substantial labeled data from various subjects collected directly by th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	478,454
2312.02178	Hierarchical ML Codebook Design for Extreme MIMO Beam Management	Beam management is a strategy to unify beamforming and channel state information (CSI) acquisition with large antenna arrays in 5G. Codebooks serve multiple uses in beam management including beamforming reference signals, CSI reporting, and analog beam training. In this paper, we propose and evaluate a machine learning...	false	false	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	false	412,736
2005.08374	Intelligent O-RAN for Beyond 5G and 6G Wireless Networks	Building on the principles of openness and intelligence, there has been a concerted global effort from the operators towards enhancing the radio access network (RAN) architecture. The objective is to build an operator-defined RAN architecture (and associated interfaces) on open hardware that provides intelligent radio ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	177,597
1911.07410	Multi-Temporal Recurrent Neural Networks For Progressive Non-Uniform Single Image Deblurring With Incremental Temporal Training	Multi-scale (MS) approaches have been widely investigated for blind single image / video deblurring that sequentially recovers deblurred images in low spatial scale first and then in high spatial scale later with the output of lower scales. MS approaches have been effective especially for severe blurs induced by large ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	153,837

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