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
2006.16648	Associations between finger tapping, gait and fall risk with application to fall risk assessment	As the world ages, elderly care becomes a big concern of the society. To address the elderly's issues on dementia and fall risk, we have investigated smart cognitive and fall risk assessment with machine learning methodology based on the data collected from finger tapping test and Timed Up and Go (TUG) test. Meanwhile,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	184,870
1906.00230	Improving VAEs' Robustness to Adversarial Attack	Variational autoencoders (VAEs) have recently been shown to be vulnerable to adversarial attacks, wherein they are fooled into reconstructing a chosen target image. However, how to defend against such attacks remains an open problem. We make significant advances in addressing this issue by introducing methods for produ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	133,316
2406.13777	Game of LLMs: Discovering Structural Constructs in Activities using Large Language Models	Human Activity Recognition is a time-series analysis problem. A popular analysis procedure used by the community assumes an optimal window length to design recognition pipelines. However, in the scenario of smart homes, where activities are of varying duration and frequency, the assumption of a constant sized window do...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	465,993
2401.15657	Data-Free Generalized Zero-Shot Learning	Deep learning models have the ability to extract rich knowledge from large-scale datasets. However, the sharing of data has become increasingly challenging due to concerns regarding data copyright and privacy. Consequently, this hampers the effective transfer of knowledge from existing data to novel downstream tasks an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	424,537
1602.04286	Geometric Adaptive Control of Attitude Dynamics on SO(3) with State Inequality Constraints	This paper presents a new geometric adaptive control system with state inequality constraints for the attitude dynamics of a rigid body. The control system is designed such that the desired attitude is asymptotically stabilized, while the controlled attitude trajectory avoids undesired regions defined by an inequality ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	52,106
2307.05330	The Value of Chess Squares	We propose a neural network-based approach to calculate the value of a chess square-piece combination. Our model takes a triplet (Color, Piece, Square) as an input and calculates a value that measures the advantage/disadvantage of having this piece on this square. Our methods build on recent advances in chess AI, and c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	378,695
2104.08568	Wide-Baseline Multi-Camera Calibration using Person Re-Identification	We address the problem of estimating the 3D pose of a network of cameras for large-environment wide-baseline scenarios, e.g., cameras for construction sites, sports stadiums, and public spaces. This task is challenging since detecting and matching the same 3D keypoint observed from two very different camera views is di...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	230,856
2405.09925	ACES: A Teleoperated Robotic Solution to Pipe Inspection from the Inside	This paper presents the definition of a teleoperated robotic system for non-destructive corrosion inspection of Steel Cylinder Concrete Pipes (SCCP) from the inside. A general description of in-pipe environment and a state of the art of in-pipe navigation solutions are exposed, with a zoom on the characteristics of the...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	454,583
2407.09084	Perceived Time To Collision as Public Space Users' Discomfort Metric	Micro-mobility transport vehicles such as e-scooters are joining current sidewalk users and affect the safety and comfort of pedestrians as primary sidewalk users. The lack of agreed-upon metrics to quantify people's discomfort hinders shared public space safety research. We introduce perceived Time To Collision (TTC) ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	472,447
2205.01054	A Change Dynamic Model for the Online Detection of Gradual Change	Changes in the statistical properties of a stochastic process are typically assumed to occur via change-points, which demark instantaneous moments of complete and total change in process behavior. In cases where these transitions occur gradually, this assumption can result in a reduced ability to properly identify and ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	294,459
2306.07301	Novel Regression and Least Square Support Vector Machine Learning Technique for Air Pollution Forecasting	Air pollution is the origination of particulate matter, chemicals, or biological substances that brings pain to either humans or other living creatures or instigates discomfort to the natural habitat and the airspace. Hence, air pollution remains one of the paramount environmental issues as far as metropolitan cities a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	372,968
2409.17642	AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure	Large language model (LLM)-based AI delegates are increasingly utilized to act on behalf of users, assisting them with a wide range of tasks through conversational interfaces. Despite their advantages, concerns arise regarding the potential risk of privacy leaks, particularly in scenarios involving social interactions....	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	491,911
1707.03543	Computing Entropies With Nested Sampling	The Shannon entropy, and related quantities such as mutual information, can be used to quantify uncertainty and relevance. However, in practice, it can be difficult to compute these quantities for arbitrary probability distributions, particularly if the probability mass functions or densities cannot be evaluated. This ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	76,885
2406.00615	Making Recommender Systems More Knowledgeable: A Framework to Incorporate Side Information	Session-based recommender systems typically focus on using only the triplet (user_id, timestamp, item_id) to make predictions of users' next actions. In this paper, we aim to utilize side information to help recommender systems catch patterns and signals otherwise undetectable. Specifically, we propose a general framew...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	459,944
1906.04688	An Improved Analysis of Training Over-parameterized Deep Neural Networks	A recent line of research has shown that gradient-based algorithms with random initialization can converge to the global minima of the training loss for over-parameterized (i.e., sufficiently wide) deep neural networks. However, the condition on the width of the neural network to ensure the global convergence is very s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	134,804
1907.06794	2nd Place Solution to the GQA Challenge 2019	We present a simple method that achieves unexpectedly superior performance for Complex Reasoning involved Visual Question Answering. Our solution collects statistical features from high-frequency words of all the questions asked about an image and use them as accurate knowledge for answering further questions of the sa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	138,702
cmp-lg/9805004	Annotation Style Guide for the Blinker Project	This annotation style guide was created by and for the Blinker project at the University of Pennsylvania. The Blinker project was so named after the ``bilingual linker'' GUI, which was created to enable bilingual annotators to ``link'' word tokens that are mutual translations in parallel texts. The parallel text chosen...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,866
2405.17427	Reason3D: Searching and Reasoning 3D Segmentation via Large Language Model	Recent advancements in multimodal large language models (LLMs) have demonstrated significant potential across various domains, particularly in concept reasoning. However, their applications in understanding 3D environments remain limited, primarily offering textual or numerical outputs without generating dense, informa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	457,911
2301.12714	Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning	We propose A-Crab (Actor-Critic Regularized by Average Bellman error), a new practical algorithm for offline reinforcement learning (RL) in complex environments with insufficient data coverage. Our algorithm combines the marginalized importance sampling framework with the actor-critic paradigm, where the critic returns...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	342,648
2006.15009	A Unifying Framework for Reinforcement Learning and Planning	Sequential decision making, commonly formalized as optimization of a Markov Decision Process, is a key challenge in artificial intelligence. Two successful approaches to MDP optimization are reinforcement learning and planning, which both largely have their own research communities. However, if both research fields sol...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	184,392
2112.07610	Improving Compositional Generalization with Latent Structure and Data Augmentation	Generic unstructured neural networks have been shown to struggle on out-of-distribution compositional generalization. Compositional data augmentation via example recombination has transferred some prior knowledge about compositionality to such black-box neural models for several semantic parsing tasks, but this often r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	271,536
2109.03537	On the Transferability of Pre-trained Language Models: A Study from Artificial Datasets	Pre-training language models (LMs) on large-scale unlabeled text data makes the model much easier to achieve exceptional downstream performance than their counterparts directly trained on the downstream tasks. In this work, we study what specific traits in the pre-training data, other than the semantics, make a pre-tra...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	254,100
2406.01781	DEFT: Efficient Fine-Tuning of Diffusion Models by Learning the Generalised $h$-transform	Generative modelling paradigms based on denoising diffusion processes have emerged as a leading candidate for conditional sampling in inverse problems. In many real-world applications, we often have access to large, expensively trained unconditional diffusion models, which we aim to exploit for improving conditional sa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	460,458
1803.01934	The morphospace of language networks	Language can be described as a network of interacting objects with different qualitative properties and complexity. These networks include semantic, syntactic, or phonological levels and have been found to provide a new picture of language complexity and its evolution. A general approach considers language from an info...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	91,960
2203.01170	Efficient Online Linear Control with Stochastic Convex Costs and Unknown Dynamics	We consider the problem of controlling an unknown linear dynamical system under a stochastic convex cost and full feedback of both the state and cost function. We present a computationally efficient algorithm that attains an optimal $\sqrt{T}$ regret-rate compared to the best stabilizing linear controller in hindsight....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	283,275
0710.5666	The Entropy Photon-Number Inequality and its Consequences	Determining the ultimate classical information carrying capacity of electromagnetic waves requires quantum-mechanical analysis to properly account for the bosonic nature of these waves. Recent work has established capacity theorems for bosonic single-user, broadcast, and wiretap channels, under the presumption of two m...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	853
2011.02912	Causal Expectation-Maximisation	Structural causal models are the basic modelling unit in Pearl's causal theory; in principle they allow us to solve counterfactuals, which are at the top rung of the ladder of causation. But they often contain latent variables that limit their application to special settings. This appears to be a consequence of the fac...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	205,079
2112.03595	State-of-the-art predictive and prescriptive analytics for IEEE CIS 3rd Technical Challenge	In this paper, we describe our proposed methodology to approach the predict+optimise challenge introduced in the IEEE CIS 3rd Technical Challenge. The predictive model employs an ensemble of LightGBM models and the prescriptive analysis employs mathematical optimisation to efficiently prescribe solutions that minimise ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	270,270
2106.11355	Port-Hamiltonian System Identification from Noisy Frequency Response Data	We present a new method for the identification of linear time-invariant passive systems from noisy frequency response data. In particular, we propose to fit a parametrized port-Hamiltonian (pH) system, which is automatically passive, to supplied data with respect to a least-squares objective function. In a numerical st...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	242,364
2012.05667	On the Secrecy Capacity of MIMO Wiretap Channels: Convex Reformulation and Efficient Numerical Methods	This paper presents novel numerical approaches to finding the secrecy capacity of the multiple-input multiple-output (MIMO) wiretap channel subject to multiple linear transmit covariance constraints, including sum power constraint, per antenna power constraints and interference power constraint. An analytical solution ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	210,857
2406.03078	Towards Federated Domain Unlearning: Verification Methodologies and Challenges	Federated Learning (FL) has evolved as a powerful tool for collaborative model training across multiple entities, ensuring data privacy in sensitive sectors such as healthcare and finance. However, the introduction of the Right to Be Forgotten (RTBF) poses new challenges, necessitating federated unlearning to delete da...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	461,081
1307.1461	Degrees of Freedom of the Rank-deficient Interference Channel with Feedback	We investigate the total degrees of freedom (DoF) of the K-user rank-deficient interference channel with feedback. For the two-user case, we characterize the total DoF by developing an achievable scheme and deriving a matching upper bound. For the three-user case, we develop a new achievable scheme which employs interf...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	25,632
2501.04881	Geophysical inverse problems with measurement-guided diffusion models	Solving inverse problems with the reverse process of a diffusion model represents an appealing avenue to produce highly realistic, yet diverse solutions from incomplete and possibly noisy measurements, ultimately enabling uncertainty quantification at scale. However, because of the intractable nature of the score funct...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	523,381
2107.03104	MACCIF-TDNN: Multi aspect aggregation of channel and context interdependence features in TDNN-based speaker verification	Most of the recent state-of-the-art results for speaker verification are achieved by X-vector and its subsequent variants. In this paper, we propose a new network architecture which aggregates the channel and context interdependence features from multi aspect based on Time Delay Neural Network (TDNN). Firstly, we use t...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	245,056
1807.08716	NullaNet: Training Deep Neural Networks for Reduced-Memory-Access Inference	Deep neural networks have been successfully deployed in a wide variety of applications including computer vision and speech recognition. However, computational and storage complexity of these models has forced the majority of computations to be performed on high-end computing platforms or on the cloud. To cope with com...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	103,600
2012.03749	Explainable AI for Interpretable Credit Scoring	With the ever-growing achievements in Artificial Intelligence (AI) and the recent boosted enthusiasm in Financial Technology (FinTech), applications such as credit scoring have gained substantial academic interest. Credit scoring helps financial experts make better decisions regarding whether or not to accept a loan ap...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	210,237
2109.05464	Sliding-mode theory under feedback constraints and the problem of epidemic control	One of the most important branches of nonlinear control theory is the so-called sliding-mode. Its aim is the design of a (nonlinear) feedback law that brings and maintains the state trajectory of a dynamic system on a given sliding surface. Here, dynamics becomes completely independent of the model parameters and can b...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	254,800
2307.00142	BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting	Short-term forecasting of residential and commercial building energy consumption is widely used in power systems and continues to grow in importance. Data-driven short-term load forecasting (STLF), although promising, has suffered from a lack of open, large-scale datasets with high building diversity. This has hindered...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	376,885
2306.11970	RSMT: Real-time Stylized Motion Transition for Characters	Styled online in-between motion generation has important application scenarios in computer animation and games. Its core challenge lies in the need to satisfy four critical requirements simultaneously: generation speed, motion quality, style diversity, and synthesis controllability. While the first two challenges deman...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	374,779
2210.10983	PSA-Det3D: Pillar Set Abstraction for 3D object Detection	Small object detection for 3D point cloud is a challenging problem because of two limitations: (1) Perceiving small objects is much more diffcult than normal objects due to the lack of valid points. (2) Small objects are easily blocked which breaks the shape of their meshes in 3D point cloud. In this paper, we propose ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	325,132
2403.14902	Hydro: Adaptive Query Processing of ML Queries	Query optimization in relational database management systems (DBMSs) is critical for fast query processing. The query optimizer relies on precise selectivity and cost estimates to effectively optimize queries prior to execution. While this strategy is effective for relational DBMSs, it is not sufficient for DBMSs tailo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	440,300
2501.04002	Extraction Of Cumulative Blobs From Dynamic Gestures	Gesture recognition is a perceptual user interface, which is based on CV technology that allows the computer to interpret human motions as commands, allowing users to communicate with a computer without the use of hands, thus making the mouse and keyboard superfluous. Gesture recognition's main weakness is a light cond...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	523,068
2307.14213	Soft Air Pocket Force Sensors for Large Scale Flexible Robots	Flexible robots have advantages over rigid robots in their ability to conform physically to their environment and to form a wide variety of shapes. Sensing the force applied by or to flexible robots is useful for both navigation and manipulation tasks, but it is challenging due to the need for the sensors to withstand ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	381,845
1712.09553	DeepIEP: a Peptide Sequence Model of Isoelectric Point (IEP/pI) using Recurrent Neural Networks (RNNs)	The isoelectric point (IEP or pI) is the pH where the net charge on the molecular ensemble of peptides and proteins is zero. This physical-chemical property is dependent on protonable/deprotonable sidechains and their pKa values. Here an pI prediction model is trained from a database of peptide sequences and pIs using ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	87,373
2204.03931	HINNPerf: Hierarchical Interaction Neural Network for Performance Prediction of Configurable Systems	Modern software systems are usually highly configurable, providing users with customized functionality through various configuration options. Understanding how system performance varies with different option combinations is important to determine optimal configurations that meet specific requirements. Due to the comple...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	290,482
2202.05863	Motion Correction and Volumetric Reconstruction for Fetal Functional Magnetic Resonance Imaging Data	Motion correction is an essential preprocessing step in functional Magnetic Resonance Imaging (fMRI) of the fetal brain with the aim to remove artifacts caused by fetal movement and maternal breathing and consequently to suppress erroneous signal correlations. Current motion correction approaches for fetal fMRI choose ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	280,013
1804.05018	Comparatives, Quantifiers, Proportions: A Multi-Task Model for the Learning of Quantities from Vision	The present work investigates whether different quantification mechanisms (set comparison, vague quantification, and proportional estimation) can be jointly learned from visual scenes by a multi-task computational model. The motivation is that, in humans, these processes underlie the same cognitive, non-symbolic abilit...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	94,981
math/0309389	Approximate Squaring	We study the ``approximate squaring'' map f(x) := x ceiling(x) and its behavior when iterated. We conjecture that if f is repeatedly applied to a rational number r = l/d > 1 then eventually an integer will be reached. We prove this when d=2, and provide evidence that it is true in general by giving an upper bound on th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,670
1506.02061	Entropy and Syntropy in the Context of Five-Valued Logics	This paper presents a five-valued representation of bifuzzy sets. This representation is related to a five-valued logic that uses the following values: true, false, inconsistent, incomplete and ambiguous. In the framework of five-valued representation, formulae for similarity, entropy and syntropy of bifuzzy sets are c...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	43,855
2304.12821	Zero-shot Transfer Learning of Driving Policy via Socially Adversarial Traffic Flow	Acquiring driving policies that can transfer to unseen environments is challenging when driving in dense traffic flows. The design of traffic flow is essential and previous studies are unable to balance interaction and safety-criticism. To tackle this problem, we propose a socially adversarial traffic flow. We propose ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	360,357
1702.02982	Fixing an error in Caponnetto and de Vito (2007)	The seminal paper of Caponnetto and de Vito (2007) provides minimax-optimal rates for kernel ridge regression in a very general setting. Its proof, however, contains an error in its bound on the effective dimensionality. In this note, we explain the mistake, provide a correct bound, and show that the main theorem remai...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	68,060
2202.13565	A Holistic Review on Advanced Bi-directional EV Charging Control Algorithms	The rapid growth of electric vehicles (EVs) has promised a next-generation transportation system with reduced carbon emission. The fast development of EVs and charging facilities is driving the evolution of Internet of Vehicles (IoV) to Internet of Electric Vehicles (IoEV). IoEV benefits from both smart grid and Intern...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	282,665
1705.03773	Flexible and Creative Chinese Poetry Generation Using Neural Memory	It has been shown that Chinese poems can be successfully generated by sequence-to-sequence neural models, particularly with the attention mechanism. A potential problem of this approach, however, is that neural models can only learn abstract rules, while poem generation is a highly creative process that involves not on...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	73,232
2502.09597	Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs	Large Language Models (LLMs) are increasingly used as chatbots, yet their ability to personalize responses to user preferences remains limited. We introduce PrefEval, a benchmark for evaluating LLMs' ability to infer, memorize and adhere to user preferences in a long-context conversational setting. PrefEval comprises 3...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	533,503
1902.04198	Preferences Implicit in the State of the World	Reinforcement learning (RL) agents optimize only the features specified in a reward function and are indifferent to anything left out inadvertently. This means that we must not only specify what to do, but also the much larger space of what not to do. It is easy to forget these preferences, since these preferences are ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	121,283
2111.05299	Can Information Flows Suggest Targets for Interventions in Neural Circuits?	Motivated by neuroscientific and clinical applications, we empirically examine whether observational measures of information flow can suggest interventions. We do so by performing experiments on artificial neural networks in the context of fairness in machine learning, where the goal is to induce fairness in the system...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	265,751
cs/0107032	Coupled Clustering: a Method for Detecting Structural Correspondence	This paper proposes a new paradigm and computational framework for identification of correspondences between sub-structures of distinct composite systems. For this, we define and investigate a variant of traditional data clustering, termed coupled clustering, which simultaneously identifies corresponding clusters withi...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	537,397
2107.13749	HTF: Homogeneous Tree Framework for Differentially-Private Release of Location Data	Mobile apps that use location data are pervasive, spanning domains such as transportation, urban planning and healthcare. Important use cases for location data rely on statistical queries, e.g., identifying hotspots where users work and travel. Such queries can be answered efficiently by building histograms. However, p...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	248,291
2401.09217	Neural Network-Based Successive Interference Cancellation for Non-Linear Bandlimited Channels	Reliable communication over bandlimited and non-linear channels usually requires equalization to simplify receiver processing. Equalizers that perform joint detection and decoding (JDD) achieve the highest information rates but are often too complex to implement. To address this challenge, model-based neural network (N...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	422,187
2405.02801	Mozart's Touch: A Lightweight Multi-modal Music Generation Framework Based on Pre-Trained Large Models	In recent years, AI-Generated Content (AIGC) has witnessed rapid advancements, facilitating the creation of music, images, and other artistic forms across a wide range of industries. However, current models for image- and video-to-music synthesis struggle to capture the nuanced emotions and atmosphere conveyed by visua...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	451,926
2206.13033	Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization	By ensuring differential privacy in the learning algorithms, one can rigorously mitigate the risk of large models memorizing sensitive training data. In this paper, we study two algorithms for this purpose, i.e., DP-SGD and DP-NSGD, which first clip or normalize \textit{per-sample} gradients to bound the sensitivity an...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	304,813
0812.1029	Uncovering protein interaction in abstracts and text using a novel linear model and word proximity networks	We participated in three of the protein-protein interaction subtasks of the Second BioCreative Challenge: classification of abstracts relevant for protein-protein interaction (IAS), discovery of protein pairs (IPS) and text passages characterizing protein interaction (ISS) in full text documents. We approached the abst...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	2,748
2310.08750	Search-Adaptor: Embedding Customization for Information Retrieval	Embeddings extracted by pre-trained Large Language Models (LLMs) have significant potential to improve information retrieval and search. Beyond the zero-shot setup in which they are being conventionally used, being able to take advantage of the information from the relevant query-corpus paired data can further boost th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	399,511
2301.13120	Doubly Optimal No-Regret Learning in Monotone Games	We consider online learning in multi-player smooth monotone games. Existing algorithms have limitations such as (1) being only applicable to strongly monotone games; (2) lacking the no-regret guarantee; (3) having only asymptotic or slow $O(\frac{1}{\sqrt{T}})$ last-iterate convergence rate to a Nash equilibrium. While...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	342,788
2012.00962	Anytime Control under Practical Communication Model	We investigate a novel anytime control algorithm for wireless networked control with random dropouts. The controller computes sequences of tentative future control commands using time-varying (Markovian) computational resources. The sensor-controller and controller-actuator channel states are spatial- and time-correlat...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	209,289
2310.09728	SVM based Multiclass Classifier for Gait phase Classification using Shank IMU Sensor	In this study, a gait phase classification method based on SVM multiclass classification is introduced, with a focus on the precise identification of the stance and swing phases, which are further subdivided into seven phases. Data from individual IMU sensors, such as Shank Acceleration X, Y, Z, Shank Gyro X, and Knee ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	399,914
2401.12550	UR4NNV: Neural Network Verification, Under-approximation Reachability Works!	Recently, formal verification of deep neural networks (DNNs) has garnered considerable attention, and over-approximation based methods have become popular due to their effectiveness and efficiency. However, these strategies face challenges in addressing the "unknown dilemma" concerning whether the exact output region o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	423,421
2112.00740	Collaborative Artificial Intelligence Needs Stronger Assurances Driven by Risks	Collaborative AI systems (CAISs) aim at working together with humans in a shared space to achieve a common goal. This critical setting yields hazardous circumstances that could harm human beings. Thus, building such systems with strong assurances of compliance with requirements, domain-specific standards and regulation...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	true	269,235
2109.14396	StoryDB: Broad Multi-language Narrative Dataset	This paper presents StoryDB - a broad multi-language dataset of narratives. StoryDB is a corpus of texts that includes stories in 42 different languages. Every language includes 500+ stories. Some of the languages include more than 20 000 stories. Every story is indexed across languages and labeled with tags such as a ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	257,956
2206.12214	Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection	This paper provides a systematic investigation into the various nonlinear objective functions which can be used to explore the feasible space associated with the optimal power flow problem. A total of 40 nonlinear objective functions are tested, and their results are compared to the data generated by a novel exhaustive...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	304,516
cs/0401004	Cyborg Systems as Platforms for Computer-Vision Algorithm-Development for Astrobiology	Employing the allegorical imagery from the film "The Matrix", we motivate and discuss our `Cyborg Astrobiologist' research program. In this research program, we are using a wearable computer and video camcorder in order to test and train a computer-vision system to be a field-geologist and field-astrobiologist.	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	538,080
1911.03594	Robo-PlaNet: Learning to Poke in a Day	Recently, the Deep Planning Network (PlaNet) approach was introduced as a model-based reinforcement learning method that learns environment dynamics directly from pixel observations. This architecture is useful for learning tasks in which either the agent does not have access to meaningful states (like position/velocit...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	152,687
1610.00192	A large scale study of SVM based methods for abstract screening in systematic reviews	A major task in systematic reviews is abstract screening, i.e., excluding, often hundreds or thousand of, irrelevant citations returned from a database search based on titles and abstracts. Thus, a systematic review platform that can automate the abstract screening process is of huge importance. Several methods have be...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	61,802
2410.16090	Analysing the Residual Stream of Language Models Under Knowledge Conflicts	Large language models (LLMs) can store a significant amount of factual knowledge in their parameters. However, their parametric knowledge may conflict with the information provided in the context. Such conflicts can lead to undesirable model behaviour, such as reliance on outdated or incorrect information. In this work...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	500,867
2305.06842	Emotion Recognition for Challenged People Facial Appearance in Social using Neural Network	Human communication is the vocal and non verbal signal to communicate with others. Human expression is a significant biometric object in picture and record databases of surveillance systems. Face appreciation has a serious role in biometric methods and is good-looking for plentiful applications, including visual scruti...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	363,681
2305.10413	On Consistency of Signature Using Lasso	Signatures are iterated path integrals of continuous and discrete-time processes, and their universal nonlinearity linearizes the problem of feature selection in time series data analysis. This paper studies the consistency of signature using Lasso regression, both theoretically and numerically. We establish conditions...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	365,045
1804.09790	Adaptive MPC with Chance Constraints for FIR Systems	This paper proposes an adaptive stochastic Model Predictive Control (MPC) strategy for stable linear time invariant systems in the presence of bounded disturbances. We consider multi-input multi-output systems that can be expressed by a finite impulse response model, whose parameters we estimate using a linear Recursiv...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	96,036
2205.03468	The AI Index 2022 Annual Report	Welcome to the fifth edition of the AI Index Report! The latest edition includes data from a broad set of academic, private, and nonprofit organizations as well as more self-collected data and original analysis than any previous editions, including an expanded technical performance chapter, a new survey of robotics res...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	295,288
1608.02732	On Lower Bounds for Regret in Reinforcement Learning	This is a brief technical note to clarify the state of lower bounds on regret for reinforcement learning. In particular, this paper: - Reproduces a lower bound on regret for reinforcement learning, similar to the result of Theorem 5 in the journal UCRL2 paper (Jaksch et al 2010). - Clarifies that the proposed proof...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	59,595
2404.12871	Expanding the Katz Index for Link Prediction: A Case Study on a Live Fish Movement Network	In aquaculture, disease spread models often neglect the dynamic interactions between farms, hindering accuracy. This study enhances the Katz index (KI) to incorporate spatial and temporal patterns of fish movement, improving the prediction of farms susceptible to disease via live fish transfers. We modified the Katz in...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	448,068
2106.08409	Benchmark dataset of memes with text transcriptions for automatic detection of multi-modal misogynistic content	In this paper we present a benchmark dataset generated as part of a project for automatic identification of misogyny within online content, which focuses in particular on memes. The benchmark here described is composed of 800 memes collected from the most popular social media platforms, such as Facebook, Twitter, Insta...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	241,277
2011.10753	Emergent Road Rules In Multi-Agent Driving Environments	For autonomous vehicles to safely share the road with human drivers, autonomous vehicles must abide by specific "road rules" that human drivers have agreed to follow. "Road rules" include rules that drivers are required to follow by law -- such as the requirement that vehicles stop at red lights -- as well as more subt...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	207,613
2502.00829	A Comprehensive Analysis on LLM-based Node Classification Algorithms	Node classification is a fundamental task in graph analysis, with broad applications across various fields. Recent breakthroughs in Large Language Models (LLMs) have enabled LLM-based approaches for this task. Although many studies demonstrate the impressive performance of LLM-based methods, the lack of clear design gu...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	529,567
1408.4994	Interference Alignment for Multicell Multiuser MIMO Uplink Channels	This paper proposes a linear interference alignment (IA) scheme which can be used for uplink channels in a general multicell multiuser MIMO cellular network. The proposed scheme aims to align interference caused by signals from a set of transmitters into a subspace which is established by the signals from only a subset...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	35,506
2405.05160	Selective Classification Under Distribution Shifts	In selective classification (SC), a classifier abstains from making predictions that are likely to be wrong to avoid excessive errors. To deploy imperfect classifiers -- either due to intrinsic statistical noise of data or for robustness issue of the classifier or beyond -- in high-stakes scenarios, SC appears to be an...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	452,815
2410.07718	Hallo2: Long-Duration and High-Resolution Audio-Driven Portrait Image Animation	Recent advances in latent diffusion-based generative models for portrait image animation, such as Hallo, have achieved impressive results in short-duration video synthesis. In this paper, we present updates to Hallo, introducing several design enhancements to extend its capabilities. First, we extend the method to prod...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	496,767
2402.09742	AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator	Artificial intelligence has significantly advanced healthcare, particularly through large language models (LLMs) that excel in medical question answering benchmarks. However, their real-world clinical application remains limited due to the complexities of doctor-patient interactions. To address this, we introduce \text...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	429,661
2105.03835	Segmenting Hybrid Trajectories using Latent ODEs	Smooth dynamics interrupted by discontinuities are known as hybrid systems and arise commonly in nature. Latent ODEs allow for powerful representation of irregularly sampled time series but are not designed to capture trajectories arising from hybrid systems. Here, we propose the Latent Segmented ODE (LatSegODE), which...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	234,289
1107.1753	Notes on Electronic Lexicography	These notes are a continuation of topics covered by V. Selegej in his article "Electronic Dictionaries and Computational lexicography". How can an electronic dictionary have as its object the description of closely related languages? Obviously, such a question allows multiple answers.	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	11,220
1606.05735	A Comparative Analysis of classification data mining techniques : Deriving key factors useful for predicting students performance	Students opting for Engineering as their discipline is increasing rapidly. But due to various factors and inappropriate primary education in India, failure rates are high. Students are unable to excel in core engineering because of complex and mathematical subjects. Hence, they fail in such subjects. With the help of d...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	57,463
2003.07781	TTDM: A Travel Time Difference Model for Next Location Prediction	Next location prediction is of great importance for many location-based applications and provides essential intelligence to business and governments. In existing studies, a common approach to next location prediction is to learn the sequential transitions with massive historical trajectories based on conditional probab...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	168,540
1910.03905	A Semi-Supervised Maximum Margin Metric Learning Approach for Small Scale Person Re-identification	In video surveillance, person re-identification is the task of searching person images in non-overlapping cameras. Though supervised methods for person re-identification have attained impressive performance, obtaining large scale cross-view labeled training data is very expensive. However, unlabelled data is available ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	148,624
1302.2223	WNtags: A Web-Based Tool For Image Labeling And Retrieval With Lexical Ontologies	Ever growing number of image documents available on the Internet continuously motivates research in better annotation models and more efficient retrieval methods. Formal knowledge representation of objects and events in pictures, their interaction as well as context complexity becomes no longer an option for a quality ...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	true	21,927
2212.12097	Tightening Quadratic Convex Relaxations for the AC Optimal Transmission Switching Problem	The Alternating Current Optimal Transmission Switching (ACOTS) problem incorporates line switching decisions into the fundamental AC optimal power flow (ACOPF) problem. The advantages of the ACOTS problem are well-known in terms of reducing the operational cost and improving system reliability. ACOTS optimization model...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	337,959
2409.13734	Enhancing Kurdish Text-to-Speech with Native Corpus Training: A High-Quality WaveGlow Vocoder Approach	The ability to synthesize spoken language from text has greatly facilitated access to digital content with the advances in text-to-speech technology. However, effective TTS development for low-resource languages, such as Central Kurdish (CKB), still faces many challenges due mainly to the lack of linguistic information...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	490,141
2009.07734	TreeGAN: Incorporating Class Hierarchy into Image Generation	Conditional image generation (CIG) is a widely studied problem in computer vision and machine learning. Given a class, CIG takes the name of this class as input and generates a set of images that belong to this class. In existing CIG works, for different classes, their corresponding images are generated independently, ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	196,030
2312.17192	HISR: Hybrid Implicit Surface Representation for Photorealistic 3D Human Reconstruction	Neural reconstruction and rendering strategies have demonstrated state-of-the-art performances due, in part, to their ability to preserve high level shape details. Existing approaches, however, either represent objects as implicit surface functions or neural volumes and still struggle to recover shapes with heterogeneo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	418,645
2203.17023	CTA-RNN: Channel and Temporal-wise Attention RNN Leveraging Pre-trained ASR Embeddings for Speech Emotion Recognition	Previous research has looked into ways to improve speech emotion recognition (SER) by utilizing both acoustic and linguistic cues of speech. However, the potential association between state-of-the-art ASR models and the SER task has yet to be investigated. In this paper, we propose a novel channel and temporal-wise att...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	289,015
1807.06093	Prognostics Estimations with Dynamic States	The health state assessment and remaining useful life (RUL) estimation play very important roles in prognostics and health management (PHM), owing to their abilities to reduce the maintenance and improve the safety of machines or equipment. However, they generally suffer from this problem of lacking prior knowledge to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	103,054
1707.00815	Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks	Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-ef...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	76,424

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.