DNNs Improve Nonparametric Estimation for Covariate-Driven Poisson Processes
DNN-based NPMLEs achieve nearly minimax-optimal rates for compositional intensities without explicit structure encoding.
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32 stories, newest first · one card per story
Stories tagged #deep-learning
arXiv releases BLE device fingerprinting dataset and testbed
Large-scale raw IQ dataset from 31 Bluetooth Low Energy devices across varied environments plus evaluation of domain-robust radio-frequency fingerprinting models.
Dissertation explores bad minima in transfer learning via adversarial attacks
Adversarial attacks on transfer learning reveal a strong link between source generalization and successful transfer.
Deep learning clutter suppression improves multistatic ISAC target estimates
Residual and attention networks beat conventional baselines on position and velocity under dense dynamic clutter.
Keystroke study models behavioral drift for continuous authentication
Fixed-text login reaches 3.77% EER; free-text monitoring reports 10.05% EER on Buffalo and GREYC data.
Any ReLU network can be exactly simulated with two hidden layers
The authors give a homological-algebra proof using fillings and a separate direct combinatorial proof.
Researchers propose SSTA to deceive cognitive radars across architectures
Authors report a 10.36% higher average black-box success rate and 0 dB main-lobe attenuation after matched filtering.
The Loss or the Architecture? What Matters in Survival Analysis with Competing Risks
A 23-dataset benchmark finds cumulative-incidence loss, not backbone choice, drives competing-risks performance.
WindBorne wins a hefty US Air Force contract for its balloon data
WindBorne won a US Air Force contract worth up to $49 million for autonomous weather-balloon data.
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Revisiting Tabular Deep Regression: Objectives and the Limits of Global Early Stopping
Tabular deep regression study finds quantile loss beats tuned MSE, but global early stopping still compromises noisy regions.
CNN-Transformer with Sigmoid Label for High-Resolution Sub-Degree DOA Estimation
A CNN-Transformer with sigmoid labels reaches sub-degree DOA accuracy on a 0.25-degree grid.
ECGWmark: Deep Watermarking for Electrocardiogram Signals
ECGWmark watermarks ECG signals without quantization and keeps over 90% bit accuracy under circular shifts.
Eigenvalues of the Hessian in Deep Learning: The Origin of Symmetry and Its Breaking
A symmetry-breaking account explains clustered Hessian spectra in trained deep networks, including ReLU, CNN, graph, and transformer models.
GCTAuto-encoder: A Cross modal Framework for Security Flaw Detection in IoT Networks
GCT auto-encoder reports 0.908 accuracy detecting IoT network intrusions from edge data.
Transcriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies
Two-stage model infers transcriptome from breast cancer histopathology to predict neoadjuvant therapy response, reaching pooled AUROC 0.79 across nine cohorts.
Planning to Learn
Horizon loss, a one-line cross-entropy modification, improves top-1 accuracy on ImageNet and MNIST, with gains increasing under label noise.
Retrieval-Centric Deep Learning in Growing Nonparametric Neural Networks
Researchers derive functional-gradient rules for retrieval-centric layers that grow by storing key-value pairs for every training point.
SoftServe: A Scalable Quasi-Newton Method for Deep Learning
SoftServe scales positive-definite quasi-Newton updates to large networks and beats Adam, Muon, and SOAP on ill-conditioned tasks.
A Structured State Space Sequence Model for Multi-Class Classification of Malware
Researchers apply a Structured State Space model to classify IoT malware from long-range execution dependencies.
Dynamics to decision: A mathematical theory of Lyapunov spectra and decision boundaries in deep classifiers
Paper ties finite-time Lyapunov exponents of deep classifiers to decision-boundary geometry.
VCRE-Fib: View-Conditioned Regional Evidence for Fine-Grained Ultrasound Grading of Schistosoma japonicum-Associated Liver Fibrosis
VCRE-Fib improves ultrasound grading of schistosomiasis liver fibrosis using view-conditioned regional evidence.
PROSWIN: Probabilistic Solar Wind Speed Forecasting Using Deep Distributional Regression From Solar Images
PROSWIN forecasts hourly solar wind speed four days ahead with calibrated probabilistic uncertainties.
IntBMoE: Integrating Block-Level Conditioning into Expert Composition for Full-Participation Mixture-of-Experts
IntBMoE is a block-conditioned Mixture-of-Experts architecture achieving full participation with sparse execution, deployed in AMap's recommendation system.
s-MDM: Generative Virtualization of Multi-Device Hardware Variations for Portable DL-SCA
Researchers present s-MDM, a generative framework synthesizing virtual device profiles to improve cross-device portability of deep learning side-channel analysis.