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
2502.00140	Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication	While Graph Neural Networks (GNNs) have achieved remarkable success, their design largely relies on empirical intuition rather than theoretical understanding. In this paper, we present a comprehensive analysis of GNN behavior through three fundamental aspects: (1) we establish that \textbf{$k$-layer} Message Passing Ne...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	true	false	false	529,228
2212.12402	Push-the-Boundary: Boundary-aware Feature Propagation for Semantic Segmentation of 3D Point Clouds	Feedforward fully convolutional neural networks currently dominate in semantic segmentation of 3D point clouds. Despite their great success, they suffer from the loss of local information at low-level layers, posing significant challenges to accurate scene segmentation and precise object boundary delineation. Prior wor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	338,032
1909.03676	Joint, Partially-joint, and Individual Independent Component Analysis in Multi-Subject fMRI Data	Objective: Joint analysis of multi-subject brain imaging datasets has wide applications in biomedical engineering. In these datasets, some sources belong to all subjects (joint), a subset of subjects (partially-joint), or a single subject (individual). In this paper, this source model is referred to as joint/partially-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	144,571
2001.06144	Learning to Augment Expressions for Few-shot Fine-grained Facial Expression Recognition	Affective computing and cognitive theory are widely used in modern human-computer interaction scenarios. Human faces, as the most prominent and easily accessible features, have attracted great attention from researchers. Since humans have rich emotions and developed musculature, there exist a lot of fine-grained expres...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	160,737
2205.13094	Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification	While a broad range of techniques have been proposed to tackle distribution shift, the simple baseline of training on an $\textit{undersampled}$ balanced dataset often achieves close to state-of-the-art-accuracy across several popular benchmarks. This is rather surprising, since undersampling algorithms discard excess ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	298,800
2409.00012	AVIN-Chat: An Audio-Visual Interactive Chatbot System with Emotional State Tuning	This work presents an audio-visual interactive chatbot (AVIN-Chat) system that allows users to have face-to-face conversations with 3D avatars in real-time. Compared to the previous chatbot services, which provide text-only or speech-only communications, the proposed AVIN-Chat can offer audio-visual communications prov...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	484,715
2012.09708	Efficient CNN-LSTM based Image Captioning using Neural Network Compression	Modern Neural Networks are eminent in achieving state of the art performance on tasks under Computer Vision, Natural Language Processing and related verticals. However, they are notorious for their voracious memory and compute appetite which further obstructs their deployment on resource limited edge devices. In order ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	212,151
2311.02231	A Gronwall Inequality Based Approach to Transient Stability Assessment for Power Grids	This paper proposes a novel Gronwall inequality-based method for transient stability assessment for power systems. The challenges of applying such methods to power systems are how to construct the differential inequality and how to treat its nonlinearity. By leveraging partial derivatives, a rotor angle difference ineq...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	405,345
2206.04841	Hierarchical mixtures of Gaussians for combined dimensionality reduction and clustering	To avoid the curse of dimensionality, a common approach to clustering high-dimensional data is to first project the data into a space of reduced dimension, and then cluster the projected data. Although effective, this two-stage approach prevents joint optimization of the dimensionality-reduction and clustering models, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	301,792
1805.09916	Multi-Task Determinantal Point Processes for Recommendation	Determinantal point processes (DPPs) have received significant attention in the recent years as an elegant model for a variety of machine learning tasks, due to their ability to elegantly model set diversity and item quality or popularity. Recent work has shown that DPPs can be effective models for product recommendati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	98,525
2009.12462	Symbolic Relational Deep Reinforcement Learning based on Graph Neural Networks and Autoregressive Policy Decomposition	We focus on reinforcement learning (RL) in relational problems that are naturally defined in terms of objects, their relations, and object-centric actions. These problems are characterized by variable state and action spaces, and finding a fixed-length representation, required by most existing RL methods, is difficult,...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	197,430
1410.3778	Parallel-Tempering Monte-Carlo Simulation with Feedback-Optimized Algorithm Applied to a Coil-to-Globule Transition of a Lattice Homopolymer	We present a study of the parallel tempering (replica exchange) Monte Carlo method, with special focus on the feedback-optimized parallel tempering algorithm, used for generating an optimal set of simulation temperatures. This method is applied to a lattice simulation of a homopolymer chain undergoing a coil-to-globule...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	36,735
1706.09667	Comparing Information-Theoretic Measures of Complexity in Boltzmann Machines	In the past three decades, many theoretical measures of complexity have been proposed to help understand complex systems. In this work, for the first time, we place these measures on a level playing field, to explore the qualitative similarities and differences between them, and their shortcomings. Specifically, using ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	76,177
2103.03689	Optimal Stationary State Estimation Over Multiple Markovian Packet Drop Channels	In this paper, we investigate the state estimation problem over multiple Markovian packet drop channels. In this problem setup, a remote estimator receives measurement data transmitted from multiple sensors over individual channels. By the method of Markovian jump linear systems, an optimal stationary estimator that mi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	223,373
2202.11312	Are We Ready for Robust and Resilient SLAM? A Framework For Quantitative Characterization of SLAM Datasets	Reliability of SLAM systems is considered one of the critical requirements in modern autonomous systems. This directed the efforts to developing many state-of-the-art systems, creating challenging datasets, and introducing rigorous metrics to measure SLAM performance. However, the link between datasets and performance ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	281,847
2109.01262	On the Accuracy of Analog Neural Network Inference Accelerators	Specialized accelerators have recently garnered attention as a method to reduce the power consumption of neural network inference. A promising category of accelerators utilizes nonvolatile memory arrays to both store weights and perform $\textit{in situ}$ analog computation inside the array. While prior work has explor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	253,383
1005.5114	Growing a Tree in the Forest: Constructing Folksonomies by Integrating Structured Metadata	Many social Web sites allow users to annotate the content with descriptive metadata, such as tags, and more recently to organize content hierarchically. These types of structured metadata provide valuable evidence for learning how a community organizes knowledge. For instance, we can aggregate many personal hierarchies...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	6,586
2106.08616	Out-of-Scope Intent Detection with Self-Supervision and Discriminative Training	Out-of-scope intent detection is of practical importance in task-oriented dialogue systems. Since the distribution of outlier utterances is arbitrary and unknown in the training stage, existing methods commonly rely on strong assumptions on data distribution such as mixture of Gaussians to make inference, resulting in ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	241,359
1905.02422	Representation of White- and Black-Box Adversarial Examples in Deep Neural Networks and Humans: A Functional Magnetic Resonance Imaging Study	The recent success of brain-inspired deep neural networks (DNNs) in solving complex, high-level visual tasks has led to rising expectations for their potential to match the human visual system. However, DNNs exhibit idiosyncrasies that suggest their visual representation and processing might be substantially different ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	129,970
2302.10804	GDBN: a Graph Neural Network Approach to Dynamic Bayesian Network	Identifying causal relations among multi-variate time series is one of the most important elements towards understanding the complex mechanisms underlying the dynamic system. It provides critical tools for forecasting, simulations and interventions in science and business analytics. In this paper, we proposed a graph n...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	346,955
2005.08347	Wake Word Detection with Alignment-Free Lattice-Free MMI	Always-on spoken language interfaces, e.g. personal digital assistants, rely on a wake word to start processing spoken input. We present novel methods to train a hybrid DNN/HMM wake word detection system from partially labeled training data, and to use it in on-line applications: (i) we remove the prerequisite of frame...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	177,589
2103.06085	On the Dual Implementation of Collision-Avoidance Constraints in Path-Following MPC for Underactuated Surface Vessels	A path-following collision-avoidance model predictive control (MPC) method is proposed which approximates obstacle shapes as convex polygons. Collision-avoidance is ensured by means of the signed distance function which is calculated efficiently as part of the MPC problem by making use of a dual formulation. The overal...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	224,182
2310.10587	A Tri-Level Optimization Model for Interdependent Infrastructure Network Resilience Against Compound Hazard Events	Resilient operation of interdependent infrastructures against compound hazard events is essential for maintaining societal well-being. To address consequence assessment challenges in this problem space, we propose a novel tri-level optimization model applied to a proof-of-concept case study with fuel distribution and t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	400,287
2312.08071	Novel View Synthesis with View-Dependent Effects from a Single Image	In this paper, we firstly consider view-dependent effects into single image-based novel view synthesis (NVS) problems. For this, we propose to exploit the camera motion priors in NVS to model view-dependent appearance or effects (VDE) as the negative disparity in the scene. By recognizing specularities "follow" the cam...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	415,187
2311.14056	DPSUR: Accelerating Differentially Private Stochastic Gradient Descent Using Selective Update and Release	Machine learning models are known to memorize private data to reduce their training loss, which can be inadvertently exploited by privacy attacks such as model inversion and membership inference. To protect against these attacks, differential privacy (DP) has become the de facto standard for privacy-preserving machine ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	409,972
2207.06815	Challenges of SLAM in extremely unstructured environments: the DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset	We present the DLR Planetary Stereo, Solid-State LiDAR, Inertial (S3LI) dataset, recorded on Mt. Etna, Sicily, an environment analogous to the Moon and Mars, using a hand-held sensor suite with attributes suitable for implementation on a space-like mobile rover. The environment is characterized by challenging condition...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	308,002
2312.17047	Inconsistency of cross-validation for structure learning in Gaussian graphical models	Despite numerous years of research into the merits and trade-offs of various model selection criteria, obtaining robust results that elucidate the behavior of cross-validation remains a challenging endeavor. In this paper, we highlight the inherent limitations of cross-validation when employed to discern the structure ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	418,606
2410.22481	Bayesian Counterfactual Prediction Models for HIV Care Retention with Incomplete Outcome and Covariate Information	Like many chronic diseases, human immunodeficiency virus (HIV) is managed over time at regular clinic visits. At each visit, patient features are assessed, treatments are prescribed, and a subsequent visit is scheduled. There is a need for data-driven methods for both predicting retention and recommending scheduling de...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	503,646
2311.04397	ToP-ToM: Trust-aware Robot Policy with Theory of Mind	Theory of Mind (ToM) is a fundamental cognitive architecture that endows humans with the ability to attribute mental states to others. Humans infer the desires, beliefs, and intentions of others by observing their behavior and, in turn, adjust their actions to facilitate better interpersonal communication and team coll...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	406,208
2411.12361	Breathless: An 8-hour Performance Contrasting Human and Robot Expressiveness	This paper describes the robot technology behind an original performance that pairs a human dancer (Cuan) with an industrial robot arm for an eight-hour dance that unfolds over the timespan of an American workday. To control the robot arm, we combine a range of sinusoidal motions with varying amplitude, frequency and o...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	509,397
2207.11209	Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise Binarization	Instance segmentation on point clouds is crucially important for 3D scene understanding. Most SOTAs adopt distance clustering, which is typically effective but does not perform well in segmenting adjacent objects with the same semantic label (especially when they share neighboring points). Due to the uneven distributio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	309,545
1801.08747	Weakly Supervised Object Detection with Pointwise Mutual Information	In this work a novel approach for weakly supervised object detection that incorporates pointwise mutual information is presented. A fully convolutional neural network architecture is applied in which the network learns one filter per object class. The resulting feature map indicates the location of objects in an image,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	88,992
1401.5098	Study of Efficient Technique Based On 2D Tsallis Entropy For Image Thresholding	Thresholding is an important task in image processing. It is a main tool in pattern recognition, image segmentation, edge detection and scene analysis. In this paper, we present a new thresholding technique based on two-dimensional Tsallis entropy. The two-dimensional Tsallis entropy was obtained from the twodimensiona...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	30,158
1810.12423	Everything you always wanted to know about a dataset: studies in data summarisation	Summarising data as text helps people make sense of it. It also improves data discovery, as search algorithms can match this text against keyword queries. In this paper, we explore the characteristics of text summaries of data in order to understand how meaningful summaries look like. We present two complementary studi...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	111,757
1503.00980	On memetic search for the max-mean dispersion problem	Given a set $V$ of $n$ elements and a distance matrix $[d_{ij}]_{n\times n}$ among elements, the max-mean dispersion problem (MaxMeanDP) consists in selecting a subset $M$ from $V$ such that the mean dispersion (or distance) among the selected elements is maximized. Being a useful model to formulate several relevant ap...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	40,770
2209.14444	Hierarchical Integration of Model Predictive and Fuzzy Logic Control for Combined Coverage and Target-Oriented Search-and-Rescue via Robots with Imperfect Sensors	Search-and-rescue (SaR) in unknown environments requires precise, optimal, and fast decisions. Robots are promising candidates for autonomously performing SaR tasks in unknown environments. While humans use their heuristics to effectively deal with uncertainties, optimisation of multiple objectives in the presence of p...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	320,247
2405.01469	Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning	AI Foundation models are gaining traction in various applications, including medical fields like radiology. However, medical foundation models are often tested on limited tasks, leaving their generalisability and biases unexplored. We present RayDINO, a large visual encoder trained by self-supervision on 873k chest X-r...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	451,360
2102.03393	MudrockNet: Semantic Segmentation of Mudrock SEM Images through Deep Learning	Segmentation and analysis of individual pores and grains of mudrocks from scanning electron microscope images is non-trivial because of noise, imaging artifacts, variation in pixel grayscale values across images, and overlaps in grayscale values among different physical features such as silt grains, clay grains, and po...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	218,729
2305.16424	SketchOGD: Memory-Efficient Continual Learning	When machine learning models are trained continually on a sequence of tasks, they are liable to forget what they learned on previous tasks -- a phenomenon known as catastrophic forgetting. Proposed solutions to catastrophic forgetting tend to involve storing information about past tasks, meaning that memory usage is a ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	368,084
2401.11646	Nonparametric Density Estimation via Variance-Reduced Sketching	Nonparametric density models are of great interest in various scientific and engineering disciplines. Classical density kernel methods, while numerically robust and statistically sound in low-dimensional settings, become inadequate even in moderate higher-dimensional settings due to the curse of dimensionality. In this...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	423,086
1412.8534	Disjunctive Normal Networks	Artificial neural networks are powerful pattern classifiers; however, they have been surpassed in accuracy by methods such as support vector machines and random forests that are also easier to use and faster to train. Backpropagation, which is used to train artificial neural networks, suffers from the herd effect probl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	38,930
2407.06779	Using Pretrained Large Language Model with Prompt Engineering to Answer Biomedical Questions	Our team participated in the BioASQ 2024 Task12b and Synergy tasks to build a system that can answer biomedical questions by retrieving relevant articles and snippets from the PubMed database and generating exact and ideal answers. We propose a two-level information retrieval and question-answering system based on pre-...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	471,530
2205.13573	Efficient Approximation of Gromov-Wasserstein Distance Using Importance Sparsification	As a valid metric of metric-measure spaces, Gromov-Wasserstein (GW) distance has shown the potential for matching problems of structured data like point clouds and graphs. However, its application in practice is limited due to the high computational complexity. To overcome this challenge, we propose a novel importance ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	298,987
2106.07432	Information exchange, meaning and redundancy generation in anticipatory systems: self-organization of expectations -- the case of Covid-19	When studying the evolution of complex systems one refers to model representations comprising various descriptive parameters. There is hardly research where system evolution is described on the base of information flows in the system. The paper focuses on the link between the dynamics of information and system evolutio...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	240,920
2005.09541	Cooperative Navigation Using Pairwise Communication with Ranging and Magnetic Anomaly Measurements	The problem of cooperative localization for a small group of Unmanned Aerial Vehicles (UAVs) in a GNSS denied environment is addressed in this paper. The presented approach contains two sequential steps: first, an algorithm called cooperative ranging localization, formulated as an Extended Kalman Filter (EKF), estimate...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	177,952
1912.05094	Associative Alignment for Few-shot Image Classification	Few-shot image classification aims at training a model from only a few examples for each of the "novel" classes. This paper proposes the idea of associative alignment for leveraging part of the base data by aligning the novel training instances to the closely related ones in the base training set. This expands the size...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	157,011
2501.01110	MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware Classification	Continual Learning (CL) for malware classification tackles the rapidly evolving nature of malware threats and the frequent emergence of new types. Generative Replay (GR)-based CL systems utilize a generative model to produce synthetic versions of past data, which are then combined with new data to retrain the primary m...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	521,930
2012.02619	Computational Complexity of Three Central Problems in Itemset Mining	Itemset mining is one of the most studied tasks in knowledge discovery. In this paper we analyze the computational complexity of three central itemset mining problems. We prove that mining confident rules with a given item in the head is NP-hard. We prove that mining high utility itemsets is NP-hard. We finally prove t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	true	209,827
1712.08244	How Well Can Generative Adversarial Networks Learn Densities: A Nonparametric View	We study in this paper the rate of convergence for learning densities under the Generative Adversarial Networks (GAN) framework, borrowing insights from nonparametric statistics. We introduce an improved GAN estimator that achieves a faster rate, through simultaneously leveraging the level of smoothness in the target d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	87,157
2408.13221	Protecting against simultaneous data poisoning attacks	Current backdoor defense methods are evaluated against a single attack at a time. This is unrealistic, as powerful machine learning systems are trained on large datasets scraped from the internet, which may be attacked multiple times by one or more attackers. We demonstrate that simultaneously executed data poisoning a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	483,054
2001.05228	Extreme Regression for Dynamic Search Advertising	This paper introduces a new learning paradigm called eXtreme Regression (XR) whose objective is to accurately predict the numerical degrees of relevance of an extremely large number of labels to a data point. XR can provide elegant solutions to many large-scale ranking and recommendation applications including Dynamic ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	160,480
2006.00276	Solution Path Algorithm for Twin Multi-class Support Vector Machine	The twin support vector machine and its extensions have made great achievements in dealing with binary classification problems. However, it suffers from difficulties in effective solution of multi-classification and fast model selection. This work devotes to the fast regularization parameter tuning algorithm for the tw...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	179,424
2003.11281	Robust Stochastic Bayesian Games for Behavior Space Coverage	A key challenge in multi-agent systems is the design of intelligent agents solving real-world tasks in close interaction with other agents (e.g. humans), thereby being confronted with a variety of behavioral variations and limited knowledge about the true behaviors of observed agents. The practicability of existing wor...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	169,565
1402.0916	Bounds on Locally Recoverable Codes with Multiple Recovering Sets	A locally recoverable code (LRC code) is a code over a finite alphabet such that every symbol in the encoding is a function of a small number of other symbols that form a recovering set. Bounds on the rate and distance of such codes have been extensively studied in the literature. In this paper we derive upper bounds o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	30,632
1608.08253	A Stackelberg Game Approach for Two-Level Distributed Energy Management in Smart Grids	The pursuit of sustainability motivates microgrids that depend on distributed resources to produce more renewable energies. An efficient operation and planning relies on a holistic framework that takes into account the interdependent decision-making of the generators of the existing power grids and the distributed reso...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	60,332
2012.13620	Teaching Robots Novel Objects by Pointing at Them	Robots that must operate in novel environments and collaborate with humans must be capable of acquiring new knowledge from human experts during operation. We propose teaching a robot novel objects it has not encountered before by pointing a hand at the new object of interest. An end-to-end neural network is used to att...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	213,275
2306.14620	Video object detection for privacy-preserving patient monitoring in intensive care	Patient monitoring in intensive care units, although assisted by biosensors, needs continuous supervision of staff. To reduce the burden on staff members, IT infrastructures are built to record monitoring data and develop clinical decision support systems. These systems, however, are vulnerable to artifacts (e.g. muscl...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	375,751
1809.00084	Understanding Neural Pathways in Zebrafish through Deep Learning and High Resolution Electron Microscope Data	The tracing of neural pathways through large volumes of image data is an incredibly tedious and time-consuming process that significantly encumbers progress in neuroscience. We are exploring deep learning's potential to automate segmentation of high-resolution scanning electron microscope (SEM) image data to remove tha...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	106,485
2001.02968	How to trap a gradient flow	We consider the problem of finding an $\varepsilon$-approximate stationary point of a smooth function on a compact domain of $\mathbb{R}^d$. In contrast with dimension-free approaches such as gradient descent, we focus here on the case where $d$ is finite, and potentially small. This viewpoint was explored in 1993 by V...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	159,852
1608.06451	Failure Detection for Facial Landmark Detectors	Most face applications depend heavily on the accuracy of the face and facial landmarks detectors employed. Prediction of attributes such as gender, age, and identity usually completely fail when the faces are badly aligned due to inaccurate facial landmark detection. Despite the impressive recent advances in face and f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	60,117
2305.13591	A Single Multi-Task Deep Neural Network with a Multi-Scale Feature Aggregation Mechanism for Manipulation Relationship Reasoning in Robotic Grasping	Grasping specific objects in complex and irregularly stacked scenes is still challenging for robotics. Because the robot is not only required to identify the object's grasping posture but also needs to reason the manipulation relationship between the objects. In this paper, we propose a manipulation relationship reason...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	366,569
2104.10563	Photothermal-SR-Net: A Customized Deep Unfolding Neural Network for Photothermal Super Resolution Imaging	This paper presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super resolution (SR) imaging. Photothermal imaging is a well-known technique in active thermography for nondestructive inspection of defects in materials such as metals or composites. A grand challenge of ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	231,626
2202.08173	Distributed k-Means with Outliers in General Metrics	Center-based clustering is a pivotal primitive for unsupervised learning and data analysis. A popular variant is undoubtedly the k-means problem, which, given a set $P$ of points from a metric space and a parameter $k<\|P\|$, requires to determine a subset $S$ of $k$ centers minimizing the sum of all squared distances of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	280,787
1707.05173	Trial without Error: Towards Safe Reinforcement Learning via Human Intervention	AI systems are increasingly applied to complex tasks that involve interaction with humans. During training, such systems are potentially dangerous, as they haven't yet learned to avoid actions that could cause serious harm. How can an AI system explore and learn without making a single mistake that harms humans or othe...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	77,179
2111.03814	Compensation of Reactive Power in Grid-Connected Solar PV Array System Using STATCOM and Fixed Capacitor Bank	In this article, we propose reactive compensation for the PV integrated grid system using a STATCOM and a fixed capacitor bank. This paper presents a design calculation for a PV integrated grid system with a fixed capacitor and STATCOM. The proposed system is simulated and tested using the MATLAB Simulink software pack...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	265,283
1912.03874	CNN-based Lidar Point Cloud De-Noising in Adverse Weather	Lidar sensors are frequently used in environment perception for autonomous vehicles and mobile robotics to complement camera, radar, and ultrasonic sensors. Adverse weather conditions are significantly impacting the performance of lidar-based scene understanding by causing undesired measurement points that in turn effe...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	156,714
2502.12803	Design Optimization of Musculoskeletal Humanoids with Maximization of Redundancy to Compensate for Muscle Rupture	Musculoskeletal humanoids have various biomimetic advantages, and the redundant muscle arrangement allowing for variable stiffness control is one of the most important. In this study, we focus on one feature of the redundancy, which enables the humanoid to keep moving even if one of its muscles breaks, an advantage tha...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	535,058
1809.06576	U-Net for MAV-based Penstock Inspection: an Investigation of Focal Loss in Multi-class Segmentation for Corrosion Identification	Periodical inspection and maintenance of critical infrastructure such as dams, penstocks, and locks are of significant importance to prevent catastrophic failures. Conventional manual inspection methods require inspectors to climb along a penstock to spot corrosion, rust and crack formation which is unsafe, labor-inten...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	108,093
2311.04694	Evaluating Generative Ad Hoc Information Retrieval	Recent advances in large language models have enabled the development of viable generative retrieval systems. Instead of a traditional document ranking, generative retrieval systems often directly return a grounded generated text as a response to a query. Quantifying the utility of the textual responses is essential fo...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	406,318
2203.10926	3D Multi-Object Tracking Using Graph Neural Networks with Cross-Edge Modality Attention	Online 3D multi-object tracking (MOT) has witnessed significant research interest in recent years, largely driven by demand from the autonomous systems community. However, 3D offline MOT is relatively less explored. Labeling 3D trajectory scene data at a large scale while not relying on high-cost human experts is still...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	286,736
1912.11713	Scalable Gaussian Process Regression for Kernels with a Non-Stationary Phase	The application of Gaussian processes (GPs) to large data sets is limited due to heavy memory and computational requirements. A variety of methods has been proposed to enable scalability, one of which is to exploit structure in the kernel matrix. Previous methods, however, cannot easily deal with non-stationary process...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	158,644
0903.3024	A Vector Generalization of Costa's Entropy-Power Inequality with Applications	This paper considers an entropy-power inequality (EPI) of Costa and presents a natural vector generalization with a real positive semidefinite matrix parameter. This new inequality is proved using a perturbation approach via a fundamental relationship between the derivative of mutual information and the minimum mean-sq...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,372
1010.3003	Twitter mood predicts the stock market	Behavioral economics tells us that emotions can profoundly affect individual behavior and decision-making. Does this also apply to societies at large, i.e., can societies experience mood states that affect their collective decision making? By extension is the public mood correlated or even predictive of economic indica...	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	7,907
1612.01211	Gaussian Process Model Predictive Control of Unknown Nonlinear Systems	Model Predictive Control (MPC) of an unknown system that is modelled by Gaussian Process (GP) techniques is studied in this paper. Using GP, the variances computed during the modelling and inference processes allow us to take model uncertainty into account. The main issue in using MPC to control systems modelled by GP ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	65,036
2201.05226	Towards a Data Privacy-Predictive Performance Trade-off	Machine learning is increasingly used in the most diverse applications and domains, whether in healthcare, to predict pathologies, or in the financial sector to detect fraud. One of the linchpins for efficiency and accuracy in machine learning is data utility. However, when it contains personal information, full access...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	275,320
2402.04841	Data-efficient Large Vision Models through Sequential Autoregression	Training general-purpose vision models on purely sequential visual data, eschewing linguistic inputs, has heralded a new frontier in visual understanding. These models are intended to not only comprehend but also seamlessly transit to out-of-domain tasks. However, current endeavors are hamstrung by an over-reliance on ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	427,612
2304.06322	Learning-based Spatial and Angular Information Separation for Light Field Compression	Light fields are a type of image data that capture both spatial and angular scene information by recording light rays emitted by a scene from different orientations. In this context, spatial information is defined as features that remain static regardless of perspectives, while angular information refers to features th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	357,933
2210.02343	Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning	We consider how to most efficiently leverage teleoperator time to collect data for learning robust image-based value functions and policies for sparse reward robotic tasks. To accomplish this goal, we modify the process of data collection to include more than just successful demonstrations of the desired task. Instead ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	321,613
2407.00042	Module control of network analysis in psychopathology	The network approach to characterizing psychopathology departs from traditional latent categorical and dimensional approaches. Causal interplay among symptoms contributed to dynamic psychopathology system. Therefore, analyzing the symptom clusters is critical for understanding mental disorders. Furthermore, despite ext...	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	468,691
2412.08939	Dynamic Contrastive Knowledge Distillation for Efficient Image Restoration	Knowledge distillation (KD) is a valuable yet challenging approach that enhances a compact student network by learning from a high-performance but cumbersome teacher model. However, previous KD methods for image restoration overlook the state of the student during the distillation, adopting a fixed solution space that ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,286
2010.10864	A Short Note on the Kinetics-700-2020 Human Action Dataset	We describe the 2020 edition of the DeepMind Kinetics human action dataset, which replenishes and extends the Kinetics-700 dataset. In this new version, there are at least 700 video clips from different YouTube videos for each of the 700 classes. This paper details the changes introduced for this new release of the dat...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	202,032
2303.16366	HerA Scheme: Secure Distributed Matrix Multiplication via Hermitian Codes	We consider the problem of secure distributed matrix multiplication (SDMM), where a user has two matrices and wishes to compute their product with the help of $N$ honest but curious servers under the security constraint that any information about either $A$ or $B$ is not leaked to any server. This paper presents a \emp...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	354,832
2411.17786	DreamCache: Finetuning-Free Lightweight Personalized Image Generation via Feature Caching	Personalized image generation requires text-to-image generative models that capture the core features of a reference subject to allow for controlled generation across different contexts. Existing methods face challenges due to complex training requirements, high inference costs, limited flexibility, or a combination of...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	511,606
2007.02423	Participation is not a Design Fix for Machine Learning	This paper critically examines existing modes of participation in design practice and machine learning. Cautioning against 'participation-washing', it suggests that the ML community must become attuned to possibly exploitative and extractive forms of community involvement and shift away from the prerogatives of context...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	185,736
2305.07625	Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn	Meta-learning and other approaches to few-shot learning are widely studied for image recognition, and are increasingly applied to other vision tasks such as pose estimation and dense prediction. This naturally raises the question of whether there is any few-shot meta-learning algorithm capable of generalizing across th...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	363,971
2210.13651	An Effective Approach for Multi-label Classification with Missing Labels	Compared with multi-class classification, multi-label classification that contains more than one class is more suitable in real life scenarios. Obtaining fully labeled high-quality datasets for multi-label classification problems, however, is extremely expensive, and sometimes even infeasible, with respect to annotatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	326,246
2109.00066	Informing Autonomous Deception Systems with Cyber Expert Performance Data	The performance of artificial intelligence (AI) algorithms in practice depends on the realism and correctness of the data, models, and feedback (labels or rewards) provided to the algorithm. This paper discusses methods for improving the realism and ecological validity of AI used for autonomous cyber defense by explori...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	252,988
2002.07374	Impact of Fountain Codes on GPRS channels	The rateless and information additive properties of fountain codes make them attractive for use in broadcast/multicast applications, especially in radio environments where channel characteristics vary with time and bandwidth is expensive. Conventional schemes using a combination of ARQ (Automatic Repeat reQuest) and FE...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	164,451
2403.06860	A Geospatial Approach to Predicting Desert Locust Breeding Grounds in Africa	Desert locust swarms present a major threat to agriculture and food security. Addressing this challenge, our study develops an operationally-ready model for predicting locust breeding grounds, which has the potential to enhance early warning systems and targeted control measures. We curated a dataset from the United Na...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	436,636
2411.00560	Topology and Intersection-Union Constrained Loss Function for Multi-Region Anatomical Segmentation in Ocular Images	Ocular Myasthenia Gravis (OMG) is a rare and challenging disease to detect in its early stages, but symptoms often first appear in the eye muscles, such as drooping eyelids and double vision. Ocular images can be used for early diagnosis by segmenting different regions, such as the sclera, iris, and pupil, which allows...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	504,642
1903.00122	Improving Grounded Natural Language Understanding through Human-Robot Dialog	Natural language understanding for robotics can require substantial domain- and platform-specific engineering. For example, for mobile robots to pick-and-place objects in an environment to satisfy human commands, we can specify the language humans use to issue such commands, and connect concept words like red can to ph...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	122,950
1808.10104	Modeling OWL with Rules: The ROWL Protege Plugin	In our experience, some ontology users find it much easier to convey logical statements using rules rather than OWL (or description logic) axioms. Based on recent theoretical developments on transformations between rules and description logics, we develop ROWL, a Protege plugin that allows users to enter OWL axioms by ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	106,334
2410.13749	Supervised Kernel Thinning	The kernel thinning algorithm of Dwivedi & Mackey (2024) provides a better-than-i.i.d. compression of a generic set of points. By generating high-fidelity coresets of size significantly smaller than the input points, KT is known to speed up unsupervised tasks like Monte Carlo integration, uncertainty quantification, an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	499,663
2210.04559	CLIP-Diffusion-LM: Apply Diffusion Model on Image Captioning	Image captioning task has been extensively researched by previous work. However, limited experiments focus on generating captions based on non-autoregressive text decoder. Inspired by the recent success of the denoising diffusion model on image synthesis tasks, we apply denoising diffusion probabilistic models to text ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	322,503
1509.03917	Dropping Convexity for Faster Semi-definite Optimization	We study the minimization of a convex function $f(X)$ over the set of $n\times n$ positive semi-definite matrices, but when the problem is recast as $\min_U g(U) := f(UU^\top)$, with $U \in \mathbb{R}^{n \times r}$ and $r \leq n$. We study the performance of gradient descent on $g$---which we refer to as Factored Gradi...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	46,875
2207.11354	Quantum Machine Learning for Distributed Quantum Protocols with Local Operations and Noisy Classical Communications	Distributed quantum information processing protocols such as quantum entanglement distillation and quantum state discrimination rely on local operations and classical communications (LOCC). Existing LOCC-based protocols typically assume the availability of ideal, noiseless, communication channels. In this paper, we stu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	309,601
2312.14198	ZeroShape: Regression-based Zero-shot Shape Reconstruction	We study the problem of single-image zero-shot 3D shape reconstruction. Recent works learn zero-shot shape reconstruction through generative modeling of 3D assets, but these models are computationally expensive at train and inference time. In contrast, the traditional approach to this problem is regression-based, where...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	417,531
2408.08550	String Diagram of Optimal Transports	We present a novel hierarchical framework for optimal transport (OT) using string diagrams, namely string diagrams of optimal transports. This framework reduces complex hierarchical OT problems to standard OT problems, allowing efficient synthesis of optimal hierarchical transportation plans. Our approach uses algebrai...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	481,037
2003.01966	Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement	In this paper, we propose a Hierarchical Learned Video Compression (HLVC) method with three hierarchical quality layers and a recurrent enhancement network. The frames in the first layer are compressed by an image compression method with the highest quality. Using these frames as references, we propose the Bi-Direction...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	166,823
2110.14096	Towards Robust Bisimulation Metric Learning	Learned representations in deep reinforcement learning (DRL) have to extract task-relevant information from complex observations, balancing between robustness to distraction and informativeness to the policy. Such stable and rich representations, often learned via modern function approximation techniques, can enable pr...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	263,409

Subsets and Splits

No community queries yet

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