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
2311.14098	Lead-acid battery lifetime extension in solar home systems under different operating conditions	Solar home systems (SHS) provide low-cost electricity access for rural off-grid communities. Batteries are a crucial part of the system, however they are often the first point of failure due to shorter lifetimes. Using field data, this work models the degradation of lead-acid batteries for different SHS use-cases, find...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	409,995
1708.07289	Family Shopping Recommendation System Using User Profile and Behavior Data	With the arrival of the big data era, recommendation system has been a hot technology for enterprises to streamline their sales. Recommendation algorithms for individual users have been extensively studied over the past decade. Most existing recommendation systems also focus on individual user recommendations, however ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	79,459
2005.11017	Robust Layout-aware IE for Visually Rich Documents with Pre-trained Language Models	Many business documents processed in modern NLP and IR pipelines are visually rich: in addition to text, their semantics can also be captured by visual traits such as layout, format, and fonts. We study the problem of information extraction from visually rich documents (VRDs) and present a model that combines the power...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	178,352
1701.00177	Fast counting of medium-sized rooted subgraphs	We prove that counting copies of any graph $F$ in another graph $G$ can be achieved using basic matrix operations on the adjacency matrix of $G$. Moreover, the resulting algorithm is competitive for medium-sized $F$: our algorithm recovers the best known complexity for rooted 6-clique counting and improves on the best ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	66,234
1901.07278	Ego-motion Sensor for Unmanned Aerial Vehicles Based on a Single-Board Computer	This paper describes the design and implementation of a ground-related odometry sensor suitable for micro aerial vehicles. The sensor is based on a ground-facing camera and a single-board Linux-based embedded computer with a multimedia System on a Chip (SoC). The SoC features a hardware video encoder which is used to e...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	119,180
2005.09904	BiQGEMM: Matrix Multiplication with Lookup Table For Binary-Coding-based Quantized DNNs	The number of parameters in deep neural networks (DNNs) is rapidly increasing to support complicated tasks and to improve model accuracy. Correspondingly, the amount of computations and required memory footprint increase as well. Quantization is an efficient method to address such concerns by compressing DNNs such that...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	178,031
cs/0504078	Adaptive Online Prediction by Following the Perturbed Leader	When applying aggregating strategies to Prediction with Expert Advice, the learning rate must be adaptively tuned. The natural choice of sqrt(complexity/current loss) renders the analysis of Weighted Majority derivatives quite complicated. In particular, for arbitrary weights there have been no results proven so far. T...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	538,685
2007.03742	Meta-active Learning in Probabilistically-Safe Optimization	Learning to control a safety-critical system with latent dynamics (e.g. for deep brain stimulation) requires taking calculated risks to gain information as efficiently as possible. To address this problem, we present a probabilistically-safe, meta-active learning approach to efficiently learn system dynamics and optima...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	186,141
2312.06560	Automatic Regularization for Linear MMSE Filters	In this work, we consider the problem of regularization in the design of minimum mean square error (MMSE) linear filters. Using the relationship with statistical machine learning methods, using a Bayesian approach, the regularization parameter is found from the observed signals in a simple and automatic manner. The pro...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	414,568
2003.03583	Ranking the spreading influence of nodes in complex networks based on mixing degree centrality and local structure	The safety and robustness of the network have attracted the attention of people from all walks of life, and the damage of several key nodes will lead to extremely serious consequences. In this paper, we proposed the clustering H-index mixing (CHM) centrality based on the H- index of the node itself and the relative dis...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	167,280
2207.03708	Video-based Smoky Vehicle Detection with A Coarse-to-Fine Framework	Automatic smoky vehicle detection in videos is a superior solution to the traditional expensive remote sensing one with ultraviolet-infrared light devices for environmental protection agencies. However, it is challenging to distinguish vehicle smoke from shadow and wet regions coming from rear vehicle or clutter roads,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	306,955
1609.07715	Multi-Rate Control over AWGN Channels via Analog Joint Source-Channel Coding	We consider the problem of controlling an unstable plant over an additive white Gaussian noise (AWGN) channel with a transmit power constraint, where the signaling rate of communication is larger than the sampling rate (for generating observations and applying control inputs) of the underlying plant. Such a situation i...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	61,476
2402.00715	Intent Assurance using LLMs guided by Intent Drift	Intent-Based Networking (IBN) presents a paradigm shift for network management, by promising to align intents and business objectives with network operations--in an automated manner. However, its practical realization is challenging: 1) processing intents, i.e., translate, decompose and identify the logic to fulfill th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	425,695
2310.11249	Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle	In the wake of relentless digital transformation, data-driven solutions are emerging as powerful tools to address multifarious industrial tasks such as forecasting, anomaly detection, planning, and even complex decision-making. Although data-centric R&D has been pivotal in harnessing these solutions, it often comes wit...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	400,573
2009.09439	Latent Representation Prediction Networks	Deeply-learned planning methods are often based on learning representations that are optimized for unrelated tasks. For example, they might be trained on reconstructing the environment. These representations are then combined with predictor functions for simulating rollouts to navigate the environment. We find this pri...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	196,582
1703.08770	SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays	Chest X-ray (CXR) is one of the most commonly prescribed medical imaging procedures, often with over 2-10x more scans than other imaging modalities such as MRI, CT scan, and PET scans. These voluminous CXR scans place significant workloads on radiologists and medical practitioners. Organ segmentation is a crucial step ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,640
1208.1149	Uncertainty-dependent data collection in vehicular sensor networks	Vehicular sensor networks (VSNs) are built on top of vehicular ad-hoc networks (VANETs) by equipping vehicles with sensing devices. These new technologies create a huge opportunity to extend the sensing capabilities of the existing road traffic control systems and improve their performance. Efficient utilisation of wir...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	17,955
1712.00886	Improving Object Detection from Scratch via Gated Feature Reuse	In this paper, we present a simple and parameter-efficient drop-in module for one-stage object detectors like SSD when learning from scratch (i.e., without pre-trained models). We call our module GFR (Gated Feature Reuse), which exhibits two main advantages. First, we introduce a novel gate-controlled prediction strate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,999
1811.09897	Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging	Generative models using neural network have opened a door to large-scale studies for various application domains, especially for studies that suffer from lack of real samples to obtain statistically robust inference. Typically, these generative models would train on existing data to learn the underlying distribution of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	114,352
2412.10064	Text2Cypher: Bridging Natural Language and Graph Databases	Knowledge graphs use nodes, relationships, and properties to represent arbitrarily complex data. When stored in a graph database, the Cypher query language enables efficient modeling and querying of knowledge graphs. However, using Cypher requires specialized knowledge, which can present a challenge for non-expert user...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	516,771
2103.05469	Universal Adversarial Perturbations and Image Spam Classifiers	As the name suggests, image spam is spam email that has been embedded in an image. Image spam was developed in an effort to evade text-based filters. Modern deep learning-based classifiers perform well in detecting typical image spam that is seen in the wild. In this chapter, we evaluate numerous adversarial techniques...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	223,992
2102.07611	Colored Kimia Path24 Dataset: Configurations and Benchmarks with Deep Embeddings	The Kimia Path24 dataset has been introduced as a classification and retrieval dataset for digital pathology. Although it provides multi-class data, the color information has been neglected in the process of extracting patches. The staining information plays a major role in the recognition of tissue patterns. To addres...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	220,156
1609.02132	UberNet: Training a `Universal' Convolutional Neural Network for Low-, Mid-, and High-Level Vision using Diverse Datasets and Limited Memory	In this work we introduce a convolutional neural network (CNN) that jointly handles low-, mid-, and high-level vision tasks in a unified architecture that is trained end-to-end. Such a universal network can act like a `swiss knife' for vision tasks; we call this architecture an UberNet to indicate its overarching natur...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	60,692
2502.05907	EvoAgent: Agent Autonomous Evolution with Continual World Model for Long-Horizon Tasks	Completing Long-Horizon (LH) tasks in open-ended worlds is an important yet difficult problem for embodied agents. Existing approaches suffer from two key challenges: (1) they heavily rely on experiences obtained from human-created data or curricula, lacking the ability to continuously update multimodal experiences, an...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	531,831
1905.08502	Mesh-based Camera Pairs Selection and Occlusion-Aware Masking for Mesh Refinement	Many Multi-View-Stereo algorithms extract a 3D mesh model of a scene, after fusing depth maps into a volumetric representation of the space. Due to the limited scalability of such representations, the estimated model does not capture fine details of the scene. Therefore a mesh refinement algorithm is usually applied; i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	131,484
2502.14023	Dynamic Activation with Knowledge Distillation for Energy-Efficient Spiking NN Ensembles	While foundation AI models excel at tasks like classification and decision-making, their high energy consumption makes them unsuitable for energy-constrained applications. Inspired by the brain's efficiency, spiking neural networks (SNNs) have emerged as a viable alternative due to their event-driven nature and compati...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	535,626
1912.05681	Mobility-Aware Smart Charging of Electric Bus Fleets	We study the joint route assignment and charge scheduling problem of a transit system dispatcher operating a fleet of electric buses in order to maximize solar energy integration and reduce energy costs. Specifically, we consider a complex bus transit system with preexisting routes, limited charging infrastructure, lim...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	157,164
1710.06255	Integrated mmWave Access and Backhaul in 5G: Bandwidth Partitioning and Downlink Analysis	With the increasing network densification, it has become exceedingly difficult to provide traditional fiber backhaul access to each cell site, which is especially true for small cell base stations (SBSs). The increasing maturity of millimeter wave (mmWave) communication has opened up the possibility of providing high-s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	82,745
0903.0460	Filtering Algorithms for the Multiset Ordering Constraint	Constraint programming (CP) has been used with great success to tackle a wide variety of constraint satisfaction problems which are computationally intractable in general. Global constraints are one of the important factors behind the success of CP. In this paper, we study a new global constraint, the multiset ordering...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	3,267
2410.15025	LLM-Driven Learning Analytics Dashboard for Teachers in EFL Writing Education	This paper presents the development of a dashboard designed specifically for teachers in English as a Foreign Language (EFL) writing education. Leveraging LLMs, the dashboard facilitates the analysis of student interactions with an essay writing system, which integrates ChatGPT for real-time feedback. The dashboard aid...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	500,328
1612.07523	Robustness of Voice Conversion Techniques Under Mismatched Conditions	Most of the existing studies on voice conversion (VC) are conducted in acoustically matched conditions between source and target signal. However, the robustness of VC methods in presence of mismatch remains unknown. In this paper, we report a comparative analysis of different VC techniques under mismatched conditions. ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	65,953
2011.11576	Conjecturing-Based Discovery of Patterns in Data	We propose the use of a conjecturing machine that suggests feature relationships in the form of bounds involving nonlinear terms for numerical features and boolean expressions for categorical features. The proposed Conjecturing framework recovers known nonlinear and boolean relationships among features from data. In bo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	207,869
2212.10520	Privacy-Preserving Domain Adaptation of Semantic Parsers	Task-oriented dialogue systems often assist users with personal or confidential matters. For this reason, the developers of such a system are generally prohibited from observing actual usage. So how can they know where the system is failing and needs more training data or new functionality? In this work, we study ways ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,497
2308.08140	GPA-3D: Geometry-aware Prototype Alignment for Unsupervised Domain Adaptive 3D Object Detection from Point Clouds	LiDAR-based 3D detection has made great progress in recent years. However, the performance of 3D detectors is considerably limited when deployed in unseen environments, owing to the severe domain gap problem. Existing domain adaptive 3D detection methods do not adequately consider the problem of the distributional disc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	385,777
2111.04556	Time- and Space-Efficient Regular Path Queries on Graphs	We introduce a time- and space-efficient technique to solve regularpath queries over labeled graphs. We combine a bit-parallel simula-tion of the Glushkov automaton of the regular expression with thering index introduced by Arroyuelo et al., exploiting its wavelettree representation of the triples in order to efficient...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	265,517
1809.10589	A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head	Purpose: To develop a deep learning approach to de-noise optical coherence tomography (OCT) B-scans of the optic nerve head (ONH). Methods: Volume scans consisting of 97 horizontal B-scans were acquired through the center of the ONH using a commercial OCT device (Spectralis) for both eyes of 20 subjects. For each eye...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	108,940
1911.00502	Review: Ordinary Differential Equations For Deep Learning	To better understand and improve the behavior of neural networks, a recent line of works bridged the connection between ordinary differential equations (ODEs) and deep neural networks (DNNs). The connections are made in two folds: (1) View DNN as ODE discretization; (2) View the training of DNN as solving an optimal co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	151,836
2211.11131	Doubly Contrastive End-to-End Semantic Segmentation for Autonomous Driving under Adverse Weather	Road scene understanding tasks have recently become crucial for self-driving vehicles. In particular, real-time semantic segmentation is indispensable for intelligent self-driving agents to recognize roadside objects in the driving area. As prior research works have primarily sought to improve the segmentation performa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,593
2411.01286	Mixed-Integer MPC-Based Motion Planning Using Hybrid Zonotopes with Tight Relaxations	Autonomous vehicle (AV) motion planning problems often involve non-convex constraints, which present a major barrier to applying model predictive control (MPC) in real time on embedded hardware. This paper presents an approach for efficiently solving mixed-integer MPC motion planning problems using a hybrid zonotope re...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	504,999
1412.3594	Large system analysis of a GLRT for detection with large sensor arrays in temporally white noise	This paper addresses the behaviour of a classical multi-antenna GLRT test that allows to detect the presence of a known signal corrupted by a multi-path propagation channel and by an additive white Gaussian noise with unknown spatial covariance matrix. The paper is focused on the case where the number of sensors M is l...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	38,304
2409.15806	CLSP: High-Fidelity Contrastive Language-State Pre-training for Agent State Representation	With the rapid development of artificial intelligence, multimodal learning has become an important research area. For intelligent agents, the state is a crucial modality to convey precise information alongside common modalities like images, videos, and language. This becomes especially clear with the broad adoption of ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	491,072
2410.13412	RAMPA: Robotic Augmented Reality for Machine Programming by DemonstrAtion	This paper introduces Robotic Augmented Reality for Machine Programming by Demonstration (RAMPA), the first ML-integrated, XR-driven end-to-end robotic system, allowing training and deployment of ML models such as ProMPs on the fly, and utilizing the capabilities of state-of-the-art and commercially available AR headse...	true	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	499,522
2108.09093	Towards Understanding the Generative Capability of Adversarially Robust Classifiers	Recently, some works found an interesting phenomenon that adversarially robust classifiers can generate good images comparable to generative models. We investigate this phenomenon from an energy perspective and provide a novel explanation. We reformulate adversarial example generation, adversarial training, and image g...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	251,492
2304.00623	MalIoT: Scalable and Real-time Malware Traffic Detection for IoT Networks	The machine learning approach is vital in Internet of Things (IoT) malware traffic detection due to its ability to keep pace with the ever-evolving nature of malware. Machine learning algorithms can quickly and accurately analyze the vast amount of data produced by IoT devices, allowing for the real-time identification...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	355,754
0906.5339	Asymmetric Quantum Cyclic Codes	It is recently conjectured in quantum information processing that phase-shift errors occur with high probability than qubit-flip errors, hence the former is more disturbing to quantum information than the later one. This leads us to construct asymmetric quantum error controlling codes to protect quantum information ove...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	4,000
2303.13793	Forecasting Competitions with Correlated Events	Beginning with Witkowski et al. [2022], recent work on forecasting competitions has addressed incentive problems with the common winner-take-all mechanism. Frongillo et al. [2021] propose a competition mechanism based on follow-the-regularized-leader (FTRL), an online learning framework. They show that their mechanism ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	353,824
cmp-lg/9411010	The "Whiteboard" Architecture: a way to integrate heterogeneous components of NLP systems	We present a new software architecture for NLP systems made of heterogeneous components, and demonstrate an architectural prototype we have built at ATR in the context of Speech Translation.	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,226
1910.05691	Analyzing User Activities Using Vector Space Model in Online Social Networks	The increasing popularity of internet, wireless technologies and mobile devices has led to the birth of mass connectivity and online interaction through Online Social Networks (OSNs) and similar environments. OSN reflects a social structure consist of a set of individuals and different types of ties like connections, r...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	149,143
2008.06993	Asymptotic Performance of Box-RLS Decoders under Imperfect CSI with Optimized Resource Allocation	This paper considers the problem of symbol detection in massive multiple-input multiple-output (MIMO) wireless communication systems. We consider hard-thresholding preceeded by two variants of the regularized least squares (RLS) decoder; namely the unconstrained RLS and the RLS with box constraint. For all schemes, we ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	191,962
2303.12147	Universal Approximation Property of Hamiltonian Deep Neural Networks	This paper investigates the universal approximation capabilities of Hamiltonian Deep Neural Networks (HDNNs) that arise from the discretization of Hamiltonian Neural Ordinary Differential Equations. Recently, it has been shown that HDNNs enjoy, by design, non-vanishing gradients, which provide numerical stability durin...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	353,151
1511.05892	Analysis and Optimization of Sparse Random Linear Network Coding for Reliable Multicast Services	Point-to-multipoint communications are expected to play a pivotal role in next-generation networks. This paper refers to a cellular system transmitting layered multicast services to a multicast group of users. Reliability of communications is ensured via different Random Linear Network Coding (RLNC) techniques. We deal...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	49,115
2305.13064	Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond	Recent research shows that when Gradient Descent (GD) is applied to neural networks, the loss almost never decreases monotonically. Instead, the loss oscillates as gradient descent converges to its ''Edge of Stability'' (EoS). Here, we find a quantity that does decrease monotonically throughout GD training: the sharpne...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	366,326
2007.12160	Online Robust and Adaptive Learning from Data Streams	In online learning from non-stationary data streams, it is necessary to learn robustly to outliers and to adapt quickly to changes in the underlying data generating mechanism. In this paper, we refer to the former attribute of online learning algorithms as robustness and to the latter as adaptivity. There is an obvious...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	188,751
1602.03368	Fast model selection by limiting SVM training times	Kernelized Support Vector Machines (SVMs) are among the best performing supervised learning methods. But for optimal predictive performance, time-consuming parameter tuning is crucial, which impedes application. To tackle this problem, the classic model selection procedure based on grid-search and cross-validation was ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	51,991
2310.04804	Ten Challenges in Industrial Recommender Systems	Huawei's vision and mission is to build a fully connected intelligent world. Since 2013, Huawei Noah's Ark Lab has helped many products build recommender systems and search engines for getting the right information to the right users. Every day, our recommender systems serve hundreds of millions of mobile phone users a...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	397,827
1103.1732	Semi-Global Approximate stabilization of an infinite dimensional quantum stochastic system	In this paper we study the semi-global (approximate) state feedback stabilization of an infinite dimensional quantum stochastic system towards a target state. A discrete-time Markov chain on an infinite-dimensional Hilbert space is used to model the dynamics of a quantum optical cavity. We can choose an (unbounded) str...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	9,540
2206.11011	Weakly-Supervised Temporal Action Localization by Progressive Complementary Learning	Weakly Supervised Temporal Action Localization (WSTAL) aims to localize and classify action instances in long untrimmed videos with only video-level category labels. Due to the lack of snippet-level supervision for indicating action boundaries, previous methods typically assign pseudo labels for unlabeled snippets. How...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	304,119
2008.04466	Conditions for the existence of a generalization of R\'enyi divergence	We give necessary and sufficient conditions for the existence of a generalization of R\'enyi divergence, which is defined in terms of a deformed exponential function. If the underlying measure $\mu$ is non-atomic, we found that not all deformed exponential functions can be used in the generalization of R\'enyi divergen...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	191,232
2112.08880	Design and Optimization for Transmissive RIS Transceiver Enabled Uplink Communication Systems	In this paper, a novel transmissive reconfigurable intelligent surface (RIS) enabled uplink communication system with orthogonal frequency division multiple access (OFDMA) is investigated. Specifically, a non-conventional receiver architecture equipped with a single receiving horn antenna and a transmissive RIS is firs...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	271,967
2306.05880	Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations	We introduce a novel modeling approach for time series imputation and forecasting, tailored to address the challenges often encountered in real-world data, such as irregular samples, missing data, or unaligned measurements from multiple sensors. Our method relies on a continuous-time-dependent model of the series' evol...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	372,370
2402.18293	Continuous Memory Representation for Anomaly Detection	There have been significant advancements in anomaly detection in an unsupervised manner, where only normal images are available for training. Several recent methods aim to detect anomalies based on a memory, comparing or reconstructing the input with directly stored normal features (or trained features with normal imag...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	433,374
2304.12550	Combining Adversaries with Anti-adversaries in Training	Adversarial training is an effective learning technique to improve the robustness of deep neural networks. In this study, the influence of adversarial training on deep learning models in terms of fairness, robustness, and generalization is theoretically investigated under more general perturbation scope that different ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	360,260
2203.16455	Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality	Recent work by Lakshminarayanan and Singh [2020] provided a dual view for fully connected deep neural networks (DNNs) with rectified linear units (ReLU). It was shown that (i) the information in the gates is analytically characterised by a kernel called the neural path kernel (NPK) and (ii) most critical information is...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	288,790
2410.05911	Accelerating Error Correction Code Transformers	Error correction codes (ECC) are crucial for ensuring reliable information transmission in communication systems. Choukroun & Wolf (2022b) recently introduced the Error Correction Code Transformer (ECCT), which has demonstrated promising performance across various transmission channels and families of codes. However, i...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	495,972
1607.08025	Mutual Information Optimally Local Private Discrete Distribution Estimation	Consider statistical learning (e.g. discrete distribution estimation) with local $\epsilon$-differential privacy, which preserves each data provider's privacy locally, we aim to optimize statistical data utility under the privacy constraints. Specifically, we study maximizing mutual information between a provider's dat...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	59,101
2209.10035	Information-theoretic Abstraction of Semantic Octree Models for Integrated Perception and Planning	In this paper, we develop an approach that enables autonomous robots to build and compress semantic environment representations from point-cloud data. Our approach builds a three-dimensional, semantic tree representation of the environment from sensor data which is then compressed by a novel information-theoretic tree-...	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	318,717
2405.13518	PerSense: Personalized Instance Segmentation in Dense Images	Leveraging large-scale pre-training, vision foundational models showcase notable performance benefits. Recent segmentation algorithms for natural scenes have advanced significantly. However, existing models still struggle to automatically segment personalized instances in dense and crowded scenarios, where severe occlu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	455,968
2409.00547	Data Augmentation for Image Classification using Generative AI	Scaling laws dictate that the performance of AI models is proportional to the amount of available data. Data augmentation is a promising solution to expanding the dataset size. Traditional approaches focused on augmentation using rotation, translation, and resizing. Recent approaches use generative AI models to improve...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	484,963
2304.03677	Scheduling Dosage of Proton Pump Inhibitors Using Constrained Optimization With Gastric Acid Secretion Model	Dosage schedule of the Proton Pump Inhibitors (PPIs) is critical for gastric acid disorder treatment. In this paper, we develop a constrained optimization based approach for scheduling the PPIs dosage. In particular, we exploit a mathematical prediction model describing the gastric acid secretion, and use it within the...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	356,902
1902.03667	Differential Similarity in Higher Dimensional Spaces: Theory and Applications	This paper presents an extension and an elaboration of the theory of differential similarity, which was originally proposed in arXiv:1401.2411 [cs.LG]. The goal is to develop an algorithm for clustering and coding that combines a geometric model with a probabilistic model in a principled way. For simplicity, the geomet...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	121,172
2207.01171	Portuguese Man-of-War Image Classification with Convolutional Neural Networks	Portuguese man-of-war (PMW) is a gelatinous organism with long tentacles capable of causing severe burns, thus leading to negative impacts on human activities, such as tourism and fishing. There is a lack of information about the spatio-temporal dynamics of this species. Therefore, the use of alternative methods for co...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	306,063
2103.13511	Addressing catastrophic forgetting for medical domain expansion	Model brittleness is a key concern when deploying deep learning models in real-world medical settings. A model that has high performance at one institution may suffer a significant decline in performance when tested at other institutions. While pooling datasets from multiple institutions and retraining may provide a st...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	226,507
2001.04251	Quantum Interference for Counting Clusters	Counting the number of clusters, when these clusters overlap significantly is a challenging problem in machine learning. We argue that a purely mathematical quantum theory, formulated using the path integral technique, when applied to non-physics modeling leads to non-physics quantum theories that are statistical in na...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	160,196
2008.05289	Speaker Conditional WaveRNN: Towards Universal Neural Vocoder for Unseen Speaker and Recording Conditions	Recent advancements in deep learning led to human-level performance in single-speaker speech synthesis. However, there are still limitations in terms of speech quality when generalizing those systems into multiple-speaker models especially for unseen speakers and unseen recording qualities. For instance, conventional n...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	191,475
1708.03474	A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing	This paper proposes a deep neural network structure that exploits edge information in addressing representative low-level vision tasks such as layer separation and image filtering. Unlike most other deep learning strategies applied in this context, our approach tackles these challenging problems by estimating edges and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,781
2404.11606	Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models	We propose a self-supervised learning approach for solving the following constrained optimization task in log-linear models or Markov networks. Let $f$ and $g$ be two log-linear models defined over the sets $\mathbf{X}$ and $\mathbf{Y}$ of random variables respectively. Given an assignment $\mathbf{x}$ to all variables...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	447,556
1103.0305	GLRT-Based Spectrum Sensing with Blindly Learned Feature under Rank-1 Assumption	Prior knowledge can improve the performance of spectrum sensing. Instead of using universal features as prior knowledge, we propose to blindly learn the localized feature at the secondary user. Motivated by pattern recognition in machine learning, we define signal feature as the leading eigenvector of the signal's samp...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,435
2405.09980	FinTextQA: A Dataset for Long-form Financial Question Answering	Accurate evaluation of financial question answering (QA) systems necessitates a comprehensive dataset encompassing diverse question types and contexts. However, current financial QA datasets lack scope diversity and question complexity. This work introduces FinTextQA, a novel dataset for long-form question answering (L...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	454,605
2304.00241	Bipartite Graph Convolutional Hashing for Effective and Efficient Top-N Search in Hamming Space	Searching on bipartite graphs is basal and versatile to many real-world Web applications, e.g., online recommendation, database retrieval, and query-document searching. Given a query node, the conventional approaches rely on the similarity matching with the vectorized node embeddings in the continuous Euclidean space. ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	355,612
2010.15740	Recurrent Neural Networks for video object detection	There is lots of scientific work about object detection in images. For many applications like for example autonomous driving the actual data on which classification has to be done are videos. This work compares different methods, especially those which use Recurrent Neural Networks to detect objects in videos. We diffe...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	203,861
1909.03050	Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification	A novel and efficient end-to-end learning model for automatic modulation classification is proposed for wireless spectrum monitoring applications, which automatically learns from the time domain in-phase and quadrature data without requiring the design of hand-crafted expert features. With the intuition of convolutiona...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	144,356
1701.06969	Error correction based on partial information	We consider the decoding of linear and array codes from errors when we are only allowed to download a part of the codeword. More specifically, suppose that we have encoded $k$ data symbols using an $(n,k)$ code with code length $n$ and dimension $k.$ During storage, some of the codeword coordinates might be corrupted b...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,215
2411.19193	Convex Regularization and Convergence of Policy Gradient Flows under Safety Constraints	This paper studies reinforcement learning (RL) in infinite-horizon dynamic decision processes with almost-sure safety constraints. Such safety-constrained decision processes are central to applications in autonomous systems, finance, and resource management, where policies must satisfy strict, state-dependent constrain...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	512,153
2406.15819	Automatic AI Model Selection for Wireless Systems: Online Learning via Digital Twinning	In modern wireless network architectures, such as O-RAN, artificial intelligence (AI)-based applications are deployed at intelligent controllers to carry out functionalities like scheduling or power control. The AI "apps" are selected on the basis of contextual information such as network conditions, topology, traffic ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	466,882
2108.13297	VTLayout: Fusion of Visual and Text Features for Document Layout Analysis	Documents often contain complex physical structures, which make the Document Layout Analysis (DLA) task challenging. As a pre-processing step for content extraction, DLA has the potential to capture rich information in historical or scientific documents on a large scale. Although many deep-learning-based methods from c...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	252,764
2404.08866	An evaluation framework for synthetic data generation models	Nowadays, the use of synthetic data has gained popularity as a cost-efficient strategy for enhancing data augmentation for improving machine learning models performance as well as addressing concerns related to sensitive data privacy. Therefore, the necessity of ensuring quality of generated synthetic data, in terms of...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	446,438
2311.05818	Learning Agile Bipedal Motions on a Quadrupedal Robot	Can a quadrupedal robot perform bipedal motions like humans? Although developing human-like behaviors is more often studied on costly bipedal robot platforms, we present a solution over a lightweight quadrupedal robot that unlocks the agility of the quadruped in an upright standing pose and is capable of a variety of h...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	406,716
1906.03560	Cross-view Semantic Segmentation for Sensing Surroundings	Sensing surroundings plays a crucial role in human spatial perception, as it extracts the spatial configuration of objects as well as the free space from the observations. To facilitate the robot perception with such a surrounding sensing capability, we introduce a novel visual task called Cross-view Semantic Segmentat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	134,415
2306.08984	Tree Variational Autoencoders	We propose Tree Variational Autoencoder (TreeVAE), a new generative hierarchical clustering model that learns a flexible tree-based posterior distribution over latent variables. TreeVAE hierarchically divides samples according to their intrinsic characteristics, shedding light on hidden structures in the data. It adapt...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	373,632
2007.08451	Specification mining and automated task planning for autonomous robots based on a graph-based spatial temporal logic	We aim to enable an autonomous robot to learn new skills from demo videos and use these newly learned skills to accomplish non-trivial high-level tasks. The goal of developing such autonomous robot involves knowledge representation, specification mining, and automated task planning. For knowledge representation, we use...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	187,628
2005.05017	Control of heat pumps with CO2 emission intensity forecasts	An optimized heat pump control for building heating was developed for minimizing CO2 emissions from related electrical power generation. The control is using weather and CO2 emission forecasts as input to a Model Predictive Control (MPC) - a multivariate control algorithm using a dynamic process model, constraints and ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	176,615
1212.0074	Challenges in Kurdish Text Processing	Despite having a large number of speakers, the Kurdish language is among the less-resourced languages. In this work we highlight the challenges and problems in providing the required tools and techniques for processing texts written in Kurdish. From a high-level perspective, the main challenges are: the inherent divers...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	20,056
2502.00734	CycleGuardian: A Framework for Automatic RespiratorySound classification Based on Improved Deep clustering and Contrastive Learning	Auscultation plays a pivotal role in early respiratory and pulmonary disease diagnosis. Despite the emergence of deep learning-based methods for automatic respiratory sound classification post-Covid-19, limited datasets impede performance enhancement. Distinguishing between normal and abnormal respiratory sounds poses ...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	529,525
2005.07308	Sensor Data for Human Activity Recognition: Feature Representation and Benchmarking	The field of Human Activity Recognition (HAR) focuses on obtaining and analysing data captured from monitoring devices (e.g. sensors). There is a wide range of applications within the field; for instance, assisted living, security surveillance, and intelligent transportation. In HAR, the development of Activity Recogni...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	177,247
2307.04721	Large Language Models as General Pattern Machines	We observe that pre-trained large language models (LLMs) are capable of autoregressively completing complex token sequences -- from arbitrary ones procedurally generated by probabilistic context-free grammars (PCFG), to more rich spatial patterns found in the Abstraction and Reasoning Corpus (ARC), a general AI benchma...	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	378,496
1706.01040	Brain Intelligence: Go Beyond Artificial Intelligence	Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	74,740
1806.04452	Transceiver Design for GFDM with Index Modulation in Multi-user Networks	Index modulation (IM) techniques can be applied to the different media in order to achieve spectral- and energy-efficient communication as well as to the indices of the subcarriers of a generalized frequency division multiplexing (GFDM) data block. In this work, a novel transceiver architecture for multi-user GFDM-IM s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	100,235
2309.13822	PARTICLE: Part Discovery and Contrastive Learning for Fine-grained Recognition	We develop techniques for refining representations for fine-grained classification and segmentation tasks in a self-supervised manner. We find that fine-tuning methods based on instance-discriminative contrastive learning are not as effective, and posit that recognizing part-specific variations is crucial for fine-grai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,366
2006.10964	A Qualitative Evaluation of Language Models on Automatic Question-Answering for COVID-19	COVID-19 has resulted in an ongoing pandemic and as of 12 June 2020, has caused more than 7.4 million cases and over 418,000 deaths. The highly dynamic and rapidly evolving situation with COVID-19 has made it difficult to access accurate, on-demand information regarding the disease. Online communities, forums, and soci...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	183,062
2111.12851	A Tractable Approach to Coverage Analysis in Downlink Satellite Networks	Satellite networks are promising to provide ubiquitous and high-capacity global wireless connectivity. Traditionally, satellite networks are modeled by placing satellites on a grid of multiple circular orbit geometries. Such a network model, however, requires intricate system-level simulations to evaluate coverage perf...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	268,093

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