A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Interactive learning improves real-time tweet classification for situational awareness.
Optimized neural networks for Edge TPU achieve high accuracy in real-time image classification.
We describe a novel spiking neural network (SNN) for automated, real-time handwritten digit classification and its implementation on a GP-GPU platform. Information processing within the network, from feature extraction to classification is implemented by mimicking the basic aspects of neuronal spike initiation and prop…
The paper uses CNNs to classify road conditions in real-time.
This paper introduces a novel real-time Fuzzy Supervised Learning with Binary Meta-Feature (FSL-BM) for big data classification task. The study of real-time algorithms addresses several major concerns, which are namely: accuracy, memory consumption, and ability to stretch assumptions and time complexity. Attaining a fa…
Framework detects anomalies in real-time PMU data.
LUNAR uses cellular automata for real-time data classification in fast streams.
SBIC improves real-time online binary classification from crowdsourced data.
Surface inspection systems are an important application domain for computer vision, as they are used for defect detection and classification in the manufacturing industry. Existing systems use hand-crafted features which require extensive domain knowledge to create. Even though Convolutional neural networks (CNNs) have…
Classifying human cognitive states from behavioral and physiological signals is a challenging problem with important applications in robotics. The problem is challenging due to the data variability among individual users, and sensor artefacts. In this work, we propose an end-to-end framework for real-time cognitive wor…
IrisNet tracks tongue contours in ultrasound videos using deep learning.
Optimizes memory and computation in wearable systems.
In (Yang et al. 2016), a hierarchical attention network (HAN) is created for document classification. The attention layer can be used to visualize text influential in classifying the document, thereby explaining the model's prediction. We successfully applied HAN to a sequential analysis task in the form of real-time m…
Recent research has demonstrated the brittleness of machine learning systems to adversarial perturbations. However, the studies have been mostly limited to perturbations on images and more generally, classification that does not deal with temporally varying inputs. In this paper we ask "Are adversarial perturbations po…
CAG method predicts nonlinear solid mechanics responses in real-time with high accuracy and efficiency.
IVMs help identify dangerous traffic conditions in real-time.
Big data trend has enforced the data-centric systems to have continuous fast data streams. In recent years, real-time analytics on stream data has formed into a new research field, which aims to answer queries about what-is-happening-now with a negligible delay. The real challenge with real-time stream data processing …
Machine learning detects and characterizes whistler radio waves for real-time monitoring of the plasmasphere.
New RL framework improves real-time control performance.
Paper proposes a log-domain training method to reduce neural network complexity.
Real-time personalization for HAR models learns from new users without prior data.
Automates detection of fast-ramped flexibility events for DSOs.
Background-Foreground classification is a well-studied problem in computer vision. Due to the pixel-wise nature of modeling and processing in the algorithm, it is usually difficult to satisfy real-time constraints. There is a trade-off between the speed (because of model complexity) and accuracy. Inspired by the reject…
Paper classifies pedestrians and vehicles detected by LiDAR.
Novel method converts time series data into functional data for high dimensional classification.
Semantic segmentation remains a computationally intensive algorithm for embedded deployment even with the rapid growth of computation power. Thus efficient network design is a critical aspect especially for applications like automated driving which requires real-time performance. Recently, there has been a lot of resea…
Neural Jump ODEs improve online filtering and classification with robust performance.
Developing a Brain-Computer Interface~(BCI) for seizure prediction can help epileptic patients have a better quality of life. However, there are many difficulties and challenges in developing such a system as a real-life support for patients. Because of the nonstationary nature of EEG signals, normal and seizure patter…
We create real-time geodesic rendering for non-isotropic geometries.
PRISM provides real-time SLAM with uncertainty estimates for agent and map states.
Stratifying patients at risk for postoperative complications may facilitate timely and accurate workups and reduce the burden of adverse events on patients and the health system. Currently, a widely-used surgical risk calculator created by the American College of Surgeons, NSQIP, uses 21 preoperative covariates to asse…
Paper proposes a new efficient transport-based dissimilarity measure for time series classification.
Improved real-time UAV terrain following with RVM-RLS filter.
FedCM measures contributions in real-time for federated learning.
Machine learning detects drilling anomalies, reducing accidents and costs.
In this paper, we use several techniques with conventional vocal feature extraction (MFCC, STFT), along with deep-learning approaches such as CNN, and also context-level analysis, by providing the textual data, and combining different approaches for improved emotion-level classification. We explore models that have not…
Random Projection (RP) technique has been widely applied in many scenarios because it can reduce high-dimensional features into low-dimensional space within short time and meet the need of real-time analysis of massive data. There is an urgent need of dimensionality reduction with fast increase of big genomics data. Ho…
Generative profiling improves real-time task timing for varied resource contexts.
Deep learning solutions are being increasingly used in mobile applications. Although there are many open-source software tools for the development of deep learning solutions, there are no guidelines in one place in a unified manner for using these tools towards real-time deployment of these solutions on smartphones. Fr…
In this paper, we introduce a novel layer designed to be used as the output of pre-trained neural networks in the context of classification. Based on Associative Memories, this layer can help design Deep Neural Networks which support incremental learning and that can be (partially) trained in real time on embedded devi…
New simulation method tackles sign problem in quantum fields.
Accurate real-time monitoring systems of influenza outbreaks help public health officials make informed decisions that may help save lives. We show that information extracted from cloud-based electronic health records databases, in combination with machine learning techniques and historical epidemiological information,…
Improved CEM for fast real-time planning in high-dimensional control tasks.
BusTr predicts bus travel times from real-time traffic forecasts.
Paper proposes real-time VaR estimation using quantile regression forest with conformal calibration.
FinBloom enhances LLMs for real-time financial queries.
Energy is a limited resource which has to be managed wisely, taking into account both supply-demand matching and capacity constraints in the distribution grid. One aspect of the smart energy management at the building level is given by the problem of real-time detection of flexible demand available. In this paper we pr…
DeepStreamCE detects new classes in streaming deep neural networks.