Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
2208.11439	A Consistency Constraint-Based Approach to Coupled State Constraints in Distributed Model Predictive Control	In this paper, we present a distributed model predictive control (DMPC) scheme for dynamically decoupled systems which are subject to state constraints, coupling state constraints and input constraints. In the proposed control scheme, neighbor-to-neighbor communication suffices and all subsystems solve their local opti...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	314,428
2108.08473	Classification of Diabetic Retinopathy Severity in Fundus Images with DenseNet121 and ResNet50	In this work, deep learning algorithms are used to classify fundus images in terms of diabetic retinopathy severity. Six different combinations of two model architectures, the Dense Convolutional Network-121 and the Residual Neural Network-50 and three image types, RGB, Green, and High Contrast, were tested to find the...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	251,261
2403.03100	NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models	While recent large-scale text-to-speech (TTS) models have achieved significant progress, they still fall short in speech quality, similarity, and prosody. Considering speech intricately encompasses various attributes (e.g., content, prosody, timbre, and acoustic details) that pose significant challenges for generation,...	false	false	true	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	435,060
2403.11563	Advancing Neuromorphic Computing: Mixed-Signal Design Techniques Leveraging Brain Code Units and Fundamental Code Units	This paper introduces a groundbreaking digital neuromorphic architecture that innovatively integrates Brain Code Unit (BCU) and Fundamental Code Unit (FCU) using mixedsignal design methodologies. Leveraging open-source datasets and the latest advances in materials science, our research focuses on enhancing the computat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	438,760
2106.08387	Towards Adversarial Robustness via Transductive Learning	There has been emerging interest to use transductive learning for adversarial robustness (Goldwasser et al., NeurIPS 2020; Wu et al., ICML 2020). Compared to traditional "test-time" defenses, these defense mechanisms "dynamically retrain" the model based on test time input via transductive learning; and theoretically, ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	241,272
2110.13242	2D Grid Map Generation for Deep-Learning-based Navigation Approaches	In the last decade, autonomous navigation for roboticshas been leveraged by deep learning and other approachesbased on machine learning. These approaches have demon-strated significant advantages in robotics performance. Butthey have the disadvantage that they require a lot of data toinfer knowledge. In this paper, we ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	263,107
2311.12574	IMGTB: A Framework for Machine-Generated Text Detection Benchmarking	In the era of large language models generating high quality texts, it is a necessity to develop methods for detection of machine-generated text to avoid harmful use or simply due to annotation purposes. It is, however, also important to properly evaluate and compare such developed methods. Recently, a few benchmarks ha...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	409,386
2403.07639	A Framework for Controlling Multiple Industrial Robots using Mobile Applications	Purpose: Over the last few decades, the development of the hardware and software has enabled the application of advanced systems. In the robotics field, the UI design is an intriguing area to be explored due to the creation of devices with a wide range of functionalities in a reduced size. Moreover, the idea of using t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	436,973
cs/0505084	An explicit formula for the number of tunnels in digital objects	An important concept in digital geometry for computer imagery is that of tunnel. In this paper we obtain a formula for the number of tunnels as a function of the number of the object vertices, pixels, holes, connected components, and 2x2 grid squares. It can be used to test for tunnel-freedom a digital object, in parti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	538,743
2006.07607	HRDNet: High-resolution Detection Network for Small Objects	Small object detection is challenging because small objects do not contain detailed information and may even disappear in the deep network. Usually, feeding high-resolution images into a network can alleviate this issue. However, simply enlarging the resolution will cause more problems, such as that, it aggravates the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	181,878
2310.16044	Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark	We introduce Stanford-ORB, a new real-world 3D Object inverse Rendering Benchmark. Recent advances in inverse rendering have enabled a wide range of real-world applications in 3D content generation, moving rapidly from research and commercial use cases to consumer devices. While the results continue to improve, there i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	402,546
1611.06241	Using LSTM recurrent neural networks for monitoring the LHC superconducting magnets	The superconducting LHC magnets are coupled with an electronic monitoring system which records and analyses voltage time series reflecting their performance. A currently used system is based on a range of preprogrammed triggers which launches protection procedures when a misbehavior of the magnets is detected. All the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	64,149
2102.09607	Modelling Paralinguistic Properties in Conversational Speech to Detect Bipolar Disorder and Borderline Personality Disorder	Bipolar disorder (BD) and borderline personality disorder (BPD) are two chronic mental health conditions that clinicians find challenging to distinguish based on clinical interviews, due to their overlapping symptoms. In this work, we investigate the automatic detection of these two conditions by modelling both verbal ...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	220,829
1812.08870	Iterative Relevance Feedback for Answer Passage Retrieval with Passage-level Semantic Match	Relevance feedback techniques assume that users provide relevance judgments for the top k (usually 10) documents and then re-rank using a new query model based on those judgments. Even though this is effective, there has been little research recently on this topic because requiring users to provide substantial feedback...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	117,054
2201.00655	Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression	Leveraging autonomous systems in safety-critical scenarios requires verifying their behaviors in the presence of uncertainties and black-box components that influence the system dynamics. In this work, we develop a framework for verifying discrete-time dynamical systems with unmodelled dynamics and noisy measurements a...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	274,027
2104.07005	Generalized Simple Streaming Codes from MDS Codes	Streaming codes represent a packet-level FEC scheme for achieving reliable, low-latency communication. In the literature on streaming codes, the commonly-assumed Gilbert-Elliott channel model, is replaced by a more tractable, delay-constrained, sliding-window (DCSW) channel model that can introduce either random or bur...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	230,266
1704.02681	Pyramid Vector Quantization for Deep Learning	This paper explores the use of Pyramid Vector Quantization (PVQ) to reduce the computational cost for a variety of neural networks (NNs) while, at the same time, compressing the weights that describe them. This is based on the fact that the dot product between an N dimensional vector of real numbers and an N dimensiona...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	71,491
1910.10300	Prioritized Inverse Kinematics: Desired Task Trajectories in Nonsingular Task Spaces	A prioritized inverse kinematics (PIK) solution can be considered as a (regulation or output tracking) control law of a dynamical system with prioritized multiple outputs. We propose a method that guarantees that a joint trajectory generated from a class of PIK solutions exists uniquely in a nonsingular configuration s...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	150,445
1911.08141	Tell Me What They're Holding: Weakly-supervised Object Detection with Transferable Knowledge from Human-object Interaction	In this work, we introduce a novel weakly supervised object detection (WSOD) paradigm to detect objects belonging to rare classes that have not many examples using transferable knowledge from human-object interactions (HOI). While WSOD shows lower performance than full supervision, we mainly focus on HOI as the main co...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	154,106
cmp-lg/9410014	A Freely Available Syntactic Lexicon for English	This paper presents a syntactic lexicon for English that was originally derived from the Oxford Advanced Learner's Dictionary and the Oxford Dictionary of Current Idiomatic English, and then modified and augmented by hand. There are more than 37,000 syntactic entries from all 8 parts of speech. An X-windows based tool ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,196
2409.07155	Compliant Blind Handover Control for Human-Robot Collaboration	This paper presents a Human-Robot Blind Handover architecture within the context of Human-Robot Collaboration (HRC). The focus lies on a blind handover scenario where the operator is intentionally faced away, focused in a task, and requires an object from the robot. In this context, it is imperative for the robot to au...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	487,407
2407.09493	Social AI and The Equation of Wittgenstein's Language User With Calvino's Literature Machine	Is it sensical to ascribe psychological predicates to AI systems like chatbots based on large language models (LLMs)? People have intuitively started ascribing emotions or consciousness to social AI ('affective artificial agents'), with consequences that range from love to suicide. The philosophical question of whether...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	472,589
2103.14076	Learning landmark geodesics using Kalman ensembles	We study the problem of diffeomorphometric geodesic landmark matching where the objective is to find a diffeomorphism that via its group action maps between two sets of landmarks. It is well-known that the motion of the landmarks, and thereby the diffeomorphism, can be encoded by an initial momentum leading to a formul...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	226,715
2405.18733	Efficient Learning in Chinese Checkers: Comparing Parameter Sharing in Multi-Agent Reinforcement Learning	We show that multi-agent reinforcement learning (MARL) with full parameter sharing outperforms independent and partially shared architectures in the competitive perfect-information homogenous game of Chinese Checkers. To run our experiments, we develop a new MARL environment: variable-size, six-player Chinese Checkers....	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	458,564
1701.00435	A Computational Approach to Finding RNA Tertiary Motifs in Genomic Sequences	Motif finding in DNA, RNA and proteins plays an important role in life science research. Recent patents concerning motif finding in the biomolecular data are recorded in the DNA Patent Database which serves as a resource for policy makers and members of the general public interested in fields like genomics, genetics an...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	66,273
2409.05732	Towards Democratizing Multilingual Large Language Models For Medicine Through A Two-Stage Instruction Fine-tuning Approach	Open-source, multilingual medical large language models (LLMs) have the potential to serve linguistically diverse populations across different regions. Adapting generic LLMs for healthcare often requires continual pretraining, but this approach is computationally expensive and sometimes impractical. Instruction fine-tu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	486,876
2202.08205	SemiRetro: Semi-template framework boosts deep retrosynthesis prediction	Recently, template-based (TB) and template-free (TF) molecule graph learning methods have shown promising results to retrosynthesis. TB methods are more accurate using pre-encoded reaction templates, and TF methods are more scalable by decomposing retrosynthesis into subproblems, i.e., center identification and synthon...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	280,801
2308.15034	Fast immersed boundary method based on weighted quadrature	Combining sum factorization, weighted quadrature, and row-based assembly enables efficient higher-order computations for tensor product splines. We aim to transfer these concepts to immersed boundary methods, which perform simulations on a regular background mesh cut by a boundary representation that defines the domain...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	388,542
2502.06301	Utilizing Novelty-based Evolution Strategies to Train Transformers in Reinforcement Learning	In this paper, we experiment with novelty-based variants of OpenAI-ES, the NS-ES and NSR-ES algorithms, and evaluate their effectiveness in training complex, transformer-based architectures designed for the problem of reinforcement learning such as Decision Transformers. We also test if we can accelerate the novelty-ba...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	532,027
2212.00502	Cellular Automata Model for Non-Structural Proteins Comparing Transmissibility and Pathogenesis of SARS Covid (CoV-2, CoV) and MERS Covid	Significantly higher transmissibility of SARS CoV-2 (2019) compared to SARS CoV (2003) can be attributed to mutations of structural proteins (Spike S, Nucleocapsid N, Membrane M, and Envelope E) and the role played by non-structural proteins (nsps) and accessory proteins (ORFs) for viral replication, assembly and shedd...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	334,085
1312.5045	Comparative analysis of evolutionary algorithms for image enhancement	Evolutionary algorithms are metaheuristic techniques that derive inspiration from the natural process of evolution. They can efficiently solve (generate acceptable quality of solution in reasonable time) complex optimization (NP-Hard) problems. In this paper, automatic image enhancement is considered as an optimization...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	29,198
2406.02548	Open-YOLO 3D: Towards Fast and Accurate Open-Vocabulary 3D Instance Segmentation	Recent works on open-vocabulary 3D instance segmentation show strong promise, but at the cost of slow inference speed and high computation requirements. This high computation cost is typically due to their heavy reliance on 3D clip features, which require computationally expensive 2D foundation models like Segment Anyt...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	460,821
1908.00086	Learning Effective Embeddings From Crowdsourced Labels: An Educational Case Study	Learning representation has been proven to be helpful in numerous machine learning tasks. The success of the majority of existing representation learning approaches often requires a large amount of consistent and noise-free labels. However, labels are not accessible in many real-world scenarios and they are usually ann...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	140,422
1909.10562	AI Matrix: A Deep Learning Benchmark for Alibaba Data Centers	Alibaba has China's largest e-commerce platform. To support its diverse businesses, Alibaba has its own large-scale data centers providing the computing foundation for a wide variety of software applications. Among these applications, deep learning (DL) has been playing an important role in delivering services like ima...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	146,577
1611.06997	Coherent Dialogue with Attention-based Language Models	We model coherent conversation continuation via RNN-based dialogue models equipped with a dynamic attention mechanism. Our attention-RNN language model dynamically increases the scope of attention on the history as the conversation continues, as opposed to standard attention (or alignment) models with a fixed input sco...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	64,294
1501.06686	Reduced Complexity Decoding of n x n Algebraic Space-Time Codes	Algebraic space-time coding allows for reliable data exchange across fading multiple-input multiple-output channels. A powerful technique for decoding space-time codes in Maximum-Likelihood (ML) decoding, but well-performing and widely-used codes such as the Golden code often suffer from high ML-decoding complexity. In...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,640
1910.11790	Measuring Conversational Fluidity in Automated Dialogue Agents	We present an automated evaluation method to measure fluidity in conversational dialogue systems. The method combines various state of the art Natural Language tools into a classifier, and human ratings on these dialogues to train an automated judgment model. Our experiments show that the results are an improvement on ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	150,882
1903.08289	GANs for Semi-Supervised Opinion Spam Detection	Online reviews have become a vital source of information in purchasing a service (product). Opinion spammers manipulate reviews, affecting the overall perception of the service. A key challenge in detecting opinion spam is obtaining ground truth. Though there exists a large set of reviews online, only a few of them hav...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	124,799
1511.01156	Robust Large-Scale Localization in 3D Point Clouds Revisited	We tackle the problem of getting a full 6-DOF pose estimation of a query image inside a given point cloud. This technical report re-evaluates the algorithms proposed by Y. Li et al. "Worldwide Pose Estimation using 3D Point Cloud". Our code computes poses from 3 or 4 points, with both known and unknown focal length. Th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	48,472
1107.1640	Nearest Neighbour Decoding with Pilot-Assisted Channel Estimation for Fading Multiple-Access Channels	We study a noncoherent multiple-input multiple-output (MIMO) fading multiple-access channel (MAC), where the transmitters and the receiver are aware of the statistics of the fading, but not of its realisation. We analyse the rate region that is achievable with nearest neighbour decoding and pilot-assisted channel estim...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	11,206
2406.18539	TexPainter: Generative Mesh Texturing with Multi-view Consistency	The recent success of pre-trained diffusion models unlocks the possibility of the automatic generation of textures for arbitrary 3D meshes in the wild. However, these models are trained in the screen space, while converting them to a multi-view consistent texture image poses a major obstacle to the output quality. In t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	468,048
2212.07132	Resilient Terrain Navigation with a 5 DOF Metal Detector Drone	Micro aerial vehicles (MAVs) hold the potential for performing autonomous and contactless land surveys for the detection of landmines and explosive remnants of war (ERW). Metal detectors are the standard detection tool but must be operated close to and parallel to the terrain. A successful combination of MAVs with meta...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	336,315
1301.7345	Codes on Lattices for Random SAF Routing	In this paper, a construction of constant weight codes based on the unique decomposition of elements in lattices is presented. The conditions for unique primary decomposition and unique irreducible decomposition in lattices are discussed and connections with the decomposition of ideals in Noetherian commutative rings e...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	21,591
1604.00834	In narrative texts punctuation marks obey the same statistics as words	From a grammar point of view, the role of punctuation marks in a sentence is formally defined and well understood. In semantic analysis punctuation plays also a crucial role as a method of avoiding ambiguity of the meaning. A different situation can be observed in the statistical analyses of language samples, where the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	54,107
2007.08696	Anisotropic Mesh Adaptation for Image Segmentation Based on Mumford-Shah Functional	As the resolution of digital images increase significantly, the processing of images becomes more challenging in terms of accuracy and efficiency. In this paper, we consider image segmentation by solving a partial differentiation equation (PDE) model based on the Mumford-Shah functional. We develop a new algorithm by c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	187,710
2203.11108	db-A*: Discontinuity-bounded Search for Kinodynamic Mobile Robot Motion Planning	We consider time-optimal motion planning for dynamical systems that are translation-invariant, a property that holds for many mobile robots, such as differential-drives, cars, airplanes, and multirotors. Our key insight is that we can extend graph-search algorithms to the continuous case when used symbiotically with op...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	286,803
1803.05885	Identifiability of dynamical networks with partial node measurements	Much recent research has dealt with the identifiability of a dynamical network in which the node signals are connected by causal linear transfer functions and are excited by known external excitation signals and/or unknown noise signals. A major research question concerns the identifiability of the whole network - topo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	92,733
1702.03429	Decoupled Sampling Based Planning Method for Multiple Autonomous Vehicles	This paper proposes a sampling based planning algorithm to control autonomous vehicles. We propose an improved Rapidly-exploring Random Tree which includes the definition of K- nearest points and propose a two-stage sampling strategy to adjust RRT in other to perform maneuver while avoiding collision. The simulation re...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	68,126
2206.05608	Gradient Boosting Performs Gaussian Process Inference	This paper shows that gradient boosting based on symmetric decision trees can be equivalently reformulated as a kernel method that converges to the solution of a certain Kernel Ridge Regression problem. Thus, we obtain the convergence to a Gaussian Process' posterior mean, which, in turn, allows us to easily transform ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,065
1812.03915	Non-Intrusive Load Monitoring with Fully Convolutional Networks	Non-intrusive load monitoring or energy disaggregation involves estimating the power consumption of individual appliances from measurements of the total power consumption of a home. Deep neural networks have been shown to be effective for energy disaggregation. In this work, we present a deep neural network architectur...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	116,105
2408.16377	ESPARGOS: Phase-Coherent WiFi CSI Datasets for Wireless Sensing Research	The use of WiFi signals to sense the physical environment is gaining popularity, with some common applications being motion detection and transmitter localization. Standard-compliant WiFi provides a cost effective, easy and backward-compatible approach to Joint Communication and Sensing and enables a seamless transfer ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	484,310
2011.11710	Natural-gradient learning for spiking neurons	In many normative theories of synaptic plasticity, weight updates implicitly depend on the chosen parametrization of the weights. This problem relates, for example, to neuronal morphology: synapses which are functionally equivalent in terms of their impact on somatic firing can differ substantially in spine size due to...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	207,904
1912.04532	Throughput Maximization for Full-Duplex UAV Aided Small Cell Wireless Systems	This paper investigates full-duplex unmanned aerial vehicle (UAV) aided small cell wireless systems, where the UAV serving as the base station (BS) is designed to transmit data to the downlink users and receive data from the uplink users simultaneously. To maximize the total system capacity, including uplink and downli...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	156,871
2203.10909	x-enVENT: A Corpus of Event Descriptions with Experiencer-specific Emotion and Appraisal Annotations	Emotion classification is often formulated as the task to categorize texts into a predefined set of emotion classes. So far, this task has been the recognition of the emotion of writers and readers, as well as that of entities mentioned in the text. We argue that a classification setup for emotion analysis should be pe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	286,729
2404.18424	PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval	Utilizing large language models (LLMs) for zero-shot document ranking is done in one of two ways: (1) prompt-based re-ranking methods, which require no further training but are only feasible for re-ranking a handful of candidate documents due to computational costs; and (2) unsupervised contrastive trained dense retrie...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	450,257
2308.15911	Cyclophobic Reinforcement Learning	In environments with sparse rewards, finding a good inductive bias for exploration is crucial to the agent's success. However, there are two competing goals: novelty search and systematic exploration. While existing approaches such as curiosity-driven exploration find novelty, they sometimes do not systematically explo...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	388,847
1808.07733	Revisiting the Importance of Encoding Logic Rules in Sentiment Classification	We analyze the performance of different sentiment classification models on syntactically complex inputs like A-but-B sentences. The first contribution of this analysis addresses reproducible research: to meaningfully compare different models, their accuracies must be averaged over far more random seeds than what has tr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	105,803
2008.06170	Privacy Preserving Vertical Federated Learning for Tree-based Models	Federated learning (FL) is an emerging paradigm that enables multiple organizations to jointly train a model without revealing their private data to each other. This paper studies {\it vertical} federated learning, which tackles the scenarios where (i) collaborating organizations own data of the same set of users but w...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	191,719
1908.00281	Featuring the topology with the unsupervised machine learning	Images of line drawings are generally composed of primitive elements. One of the most fundamental elements to characterize images is the topology; line segments belong to a category different from closed circles, and closed circles with different winding degrees are nonequivalent. We investigate images with nontrivial ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	140,478
1509.06749	Directional spin wavelets on the sphere	We construct a directional spin wavelet framework on the sphere by generalising the scalar scale-discretised wavelet transform to signals of arbitrary spin. The resulting framework is the only wavelet framework defined natively on the sphere that is able to probe the directional intensity of spin signals. Furthermore, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	47,185
2110.00673	Multi-Agent Algorithmic Recourse	The recent adoption of machine learning as a tool in real world decision making has spurred interest in understanding how these decisions are being made. Counterfactual Explanations are a popular interpretable machine learning technique that aims to understand how a machine learning model would behave if given alternat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	258,482
2410.02081	MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K Parameters	Recently, there has been a growing interest in Long-term Time Series Forecasting (LTSF), which involves predicting long-term future values by analyzing a large amount of historical time-series data to identify patterns and trends. There exist significant challenges in LTSF due to its complex temporal dependencies and h...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	494,092
2001.07752	Emergence of Pragmatics from Referential Game between Theory of Mind Agents	Pragmatics studies how context can contribute to language meanings. In human communication, language is never interpreted out of context, and sentences can usually convey more information than their literal meanings. However, this mechanism is missing in most multi-agent systems, restricting the communication efficienc...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	true	false	false	false	161,112
2402.01176	CorpusLM: Towards a Unified Language Model on Corpus for Knowledge-Intensive Tasks	Large language models (LLMs) have gained significant attention in various fields but prone to hallucination, especially in knowledge-intensive (KI) tasks. To address this, retrieval-augmented generation (RAG) has emerged as a popular solution to enhance factual accuracy. However, traditional retrieval modules often rel...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	425,899
2405.04359	A Personalizable Controller for the Walking Assistive omNi-Directional Exo-Robot (WANDER)	Preserving and encouraging mobility in the elderly and adults with chronic conditions is of paramount importance. However, existing walking aids are either inadequate to provide sufficient support to users' stability or too bulky and poorly maneuverable to be used outside hospital environments. In addition, they all la...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	452,544
2110.09678	Convergence Rate of Accelerated Average Consensus with Local Node Memory: Optimization and Analytic Solutions	Previous researches have shown that adding local memory can accelerate the consensus. It is natural to ask questions like what is the fastest rate achievable by the $M$-tap memory acceleration, and what are the corresponding control parameters. This paper introduces a set of effective and previously unused techniques t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	261,885
2201.08877	Variational Autoencoder based Metamodeling for Multi-Objective Topology Optimization of Electrical Machines	Conventional magneto-static finite element analysis of electrical machine design is time-consuming and computationally expensive. Since each machine topology has a distinct set of parameters, design optimization is commonly performed independently. This paper presents a novel method for predicting Key Performance Indic...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	276,471
2211.12081	CDDSA: Contrastive Domain Disentanglement and Style Augmentation for Generalizable Medical Image Segmentation	Generalization to previously unseen images with potential domain shifts and different styles is essential for clinically applicable medical image segmentation, and the ability to disentangle domain-specific and domain-invariant features is key for achieving Domain Generalization (DG). However, existing DG methods can h...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,985
2009.09283	Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images	Unprecedented data collection and sharing have exacerbated privacy concerns and led to increasing interest in privacy-preserving tools that remove sensitive attributes from images while maintaining useful information for other tasks. Currently, state-of-the-art approaches use privacy-preserving generative adversarial n...	false	false	false	false	true	false	true	false	false	false	false	true	true	false	false	false	false	false	196,524
2209.01642	Fraud Detection Using Optimized Machine Learning Tools Under Imbalance Classes	Fraud detection is a challenging task due to the changing nature of fraud patterns over time and the limited availability of fraud examples to learn such sophisticated patterns. Thus, fraud detection with the aid of smart versions of machine learning (ML) tools is essential to assure safety. Fraud detection is a primar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	315,965
2101.08465	FWB-Net:Front White Balance Network for Color Shift Correction in Single Image Dehazing via Atmospheric Light Estimation	In recent years, single image dehazing deep models based on Atmospheric Scattering Model (ASM) have achieved remarkable results. But the dehazing outputs of those models suffer from color shift. Analyzing the ASM model shows that the atmospheric light factor (ALF) is set as a scalar which indicates ALF is constant for ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	216,330
2402.08832	Intelligent Agricultural Management Considering N$_2$O Emission and Climate Variability with Uncertainties	This study examines how artificial intelligence (AI), especially Reinforcement Learning (RL), can be used in farming to boost crop yields, fine-tune nitrogen use and watering, and reduce nitrate runoff and greenhouse gases, focusing on Nitrous Oxide (N$_2$O) emissions from soil. Facing climate change and limited agricu...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	429,257
1711.00549	Just ASK: Building an Architecture for Extensible Self-Service Spoken Language Understanding	This paper presents the design of the machine learning architecture that underlies the Alexa Skills Kit (ASK) a large scale Spoken Language Understanding (SLU) Software Development Kit (SDK) that enables developers to extend the capabilities of Amazon's virtual assistant, Alexa. At Amazon, the infrastructure powers ove...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	false	true	83,740
2406.04484	Step Out and Seek Around: On Warm-Start Training with Incremental Data	Data often arrives in sequence over time in real-world deep learning applications such as autonomous driving. When new training data is available, training the model from scratch undermines the benefit of leveraging the learned knowledge, leading to significant training costs. Warm-starting from a previously trained ch...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	461,699
2006.15736	Roweisposes, Including Eigenposes, Supervised Eigenposes, and Fisherposes, for 3D Action Recognition	Human action recognition is one of the important fields of computer vision and machine learning. Although various methods have been proposed for 3D action recognition, some of which are basic and some use deep learning, the need of basic methods based on generalized eigenvalue problem is sensed for action recognition. ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	184,607
1404.1847	Evaluation and Ranking of Machine Translated Output in Hindi Language using Precision and Recall Oriented Metrics	Evaluation plays a crucial role in development of Machine translation systems. In order to judge the quality of an existing MT system i.e. if the translated output is of human translation quality or not, various automatic metrics exist. We here present the implementation results of different metrics when used on Hindi ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	32,150
2105.03552	Solving social dilemmas by reasoning about expectations	It has been argued that one role of social constructs, such as institutions, trust and norms, is to coordinate the expectations of autonomous entities in order to resolve collective action situations (such as collective risk dilemmas) through the coordination of behaviour. While much work has addressed the formal repre...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	234,177
2109.13692	Three New Infinite Families of Optimal Locally Repairable Codes from Matrix-Product Codes	Locally repairable codes have become a key instrument in large-scale distributed storage systems. This paper focuses on the construction of locally repairable codes with $(r,\delta)$-locality that achieve the equality in the Singleton-type bound. We use matrix-product codes to propose two infinite families of $q$-ary o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	257,711
2011.04345	BayGo: Joint Bayesian Learning and Information-Aware Graph Optimization	This article deals with the problem of distributed machine learning, in which agents update their models based on their local datasets, and aggregate the updated models collaboratively and in a fully decentralized manner. In this paper, we tackle the problem of information heterogeneity arising in multi-agent networks ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	205,556
1610.09608	A Theoretical Study of The Relationship Between Whole An ELM Network and Its Subnetworks	A biological neural network is constituted by numerous subnetworks and modules with different functionalities. For an artificial neural network, the relationship between a network and its subnetworks is also important and useful for both theoretical and algorithmic research, i.e. it can be exploited to develop incremen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	63,089
2304.07261	Frequency Decomposition to Tap the Potential of Single Domain for Generalization	Domain generalization (DG), aiming at models able to work on multiple unseen domains, is a must-have characteristic of general artificial intelligence. DG based on single source domain training data is more challenging due to the lack of comparable information to help identify domain invariant features. In this paper, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	358,287
2312.04965	Inversion-Free Image Editing with Natural Language	Despite recent advances in inversion-based editing, text-guided image manipulation remains challenging for diffusion models. The primary bottlenecks include 1) the time-consuming nature of the inversion process; 2) the struggle to balance consistency with accuracy; 3) the lack of compatibility with efficient consistenc...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	413,905
1704.00386	Local Algorithms for Hierarchical Dense Subgraph Discovery	Finding the dense regions of a graph and relations among them is a fundamental problem in network analysis. Core and truss decompositions reveal dense subgraphs with hierarchical relations. The incremental nature of algorithms for computing these decompositions and the need for global information at each step of the al...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	71,071
2107.00630	Variational Diffusion Models	Diffusion-based generative models have demonstrated a capacity for perceptually impressive synthesis, but can they also be great likelihood-based models? We answer this in the affirmative, and introduce a family of diffusion-based generative models that obtain state-of-the-art likelihoods on standard image density esti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	244,217
2003.00425	Learning When and Where to Zoom with Deep Reinforcement Learning	While high resolution images contain semantically more useful information than their lower resolution counterparts, processing them is computationally more expensive, and in some applications, e.g. remote sensing, they can be much more expensive to acquire. For these reasons, it is desirable to develop an automatic met...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	166,299
2409.15817	SwiftDossier: Tailored Automatic Dossier for Drug Discovery with LLMs and Agents	The advancement of artificial intelligence algorithms has expanded their application to several fields such as the biomedical domain. Artificial intelligence systems, including Large Language Models (LLMs), can be particularly advantageous in drug discovery, which is a very long and expensive process. However, LLMs by ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	491,080
1801.09810	Personalized Survival Prediction with Contextual Explanation Networks	Accurate and transparent prediction of cancer survival times on the level of individual patients can inform and improve patient care and treatment practices. In this paper, we design a model that concurrently learns to accurately predict patient-specific survival distributions and to explain its predictions in terms of...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	89,174
2111.14824	Learning to Fit Morphable Models	Fitting parametric models of human bodies, hands or faces to sparse input signals in an accurate, robust, and fast manner has the promise of significantly improving immersion in AR and VR scenarios. A common first step in systems that tackle these problems is to regress the parameters of the parametric model directly f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	268,720
2205.15269	Kernel Neural Optimal Transport	We study the Neural Optimal Transport (NOT) algorithm which uses the general optimal transport formulation and learns stochastic transport plans. We show that NOT with the weak quadratic cost might learn fake plans which are not optimal. To resolve this issue, we introduce kernel weak quadratic costs. We show that they...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	299,663
2305.05001	GersteinLab at MEDIQA-Chat 2023: Clinical Note Summarization from Doctor-Patient Conversations through Fine-tuning and In-context Learning	This paper presents our contribution to the MEDIQA-2023 Dialogue2Note shared task, encompassing both subtask A and subtask B. We approach the task as a dialogue summarization problem and implement two distinct pipelines: (a) a fine-tuning of a pre-trained dialogue summarization model and GPT-3, and (b) few-shot in-cont...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	362,971
1604.01416	dMath: A Scalable Linear Algebra and Math Library for Heterogeneous GP-GPU Architectures	A new scalable parallel math library, dMath, is presented in this paper that demonstrates leading scaling when using intranode, or internode, hybrid-parallelism for deep-learning. dMath provides easy-to-use distributed base primitives and a variety of domain-specific algorithms. These include matrix multiplication, con...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	54,191
2003.02020	Posterior-GAN: Towards Informative and Coherent Response Generation with Posterior Generative Adversarial Network	Neural conversational models learn to generate responses by taking into account the dialog history. These models are typically optimized over the query-response pairs with a maximum likelihood estimation objective. However, the query-response tuples are naturally loosely coupled, and there exist multiple responses that...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	166,837
2312.01050	Detection and Analysis of Stress-Related Posts in Reddit Acamedic Communities	Nowadays, the significance of monitoring stress levels and recognizing early signs of mental illness cannot be overstated. Automatic stress detection in text can proactively help manage stress and protect mental well-being. In today's digital era, social media platforms reflect the psychological well-being and stress l...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	412,287
2310.16076	Practical Computational Power of Linear Transformers and Their Recurrent and Self-Referential Extensions	Recent studies of the computational power of recurrent neural networks (RNNs) reveal a hierarchy of RNN architectures, given real-time and finite-precision assumptions. Here we study auto-regressive Transformers with linearised attention, a.k.a. linear Transformers (LTs) or Fast Weight Programmers (FWPs). LTs are speci...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	402,565
2501.05415	Uncertainty-aware Knowledge Tracing	Knowledge Tracing (KT) is crucial in education assessment, which focuses on depicting students' learning states and assessing students' mastery of subjects. With the rise of modern online learning platforms, particularly massive open online courses (MOOCs), an abundance of interaction data has greatly advanced the deve...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	523,571
2405.15625	Nonlinear denoising score matching for enhanced learning of structured distributions	We present a novel method for training score-based generative models which uses nonlinear noising dynamics to improve learning of structured distributions. Generalizing to a nonlinear drift allows for additional structure to be incorporated into the dynamics, thus making the training better adapted to the data, e.g., i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	457,024
2110.14928	Learning Actions for Drift-Free Navigation in Highly Dynamic Scenes	We embark on a hitherto unreported problem of an autonomous robot (self-driving car) navigating in dynamic scenes in a manner that reduces its localization error and eventual cumulative drift or Absolute Trajectory Error, which is pronounced in such dynamic scenes. With the hugely popular Velodyne-16 3D LIDAR as the ma...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	263,697
cs/0606066	The Cumulative Rule for Belief Fusion	The problem of combining beliefs in the Dempster-Shafer belief theory has attracted considerable attention over the last two decades. The classical Dempster's Rule has often been criticised, and many alternative rules for belief combination have been proposed in the literature. The consensus operator for combining beli...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	539,521
2202.00117	Continuous Forecasting via Neural Eigen Decomposition	Neural differential equations predict the derivative of a stochastic process. This allows irregular forecasting with arbitrary time-steps. However, the expressive temporal flexibility often comes with a high sensitivity to noise. In addition, current methods model measurements and control together, limiting generalizat...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	278,029
1309.6849	Cyclic Causal Discovery from Continuous Equilibrium Data	We propose a method for learning cyclic causal models from a combination of observational and interventional equilibrium data. Novel aspects of the proposed method are its ability to work with continuous data (without assuming linearity) and to deal with feedback loops. Within the context of biochemical reactions, we a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	27,311

Subsets and Splits

No community queries yet

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