On-device research index

arXiv research

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.

169,051 papers · 148 categories

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4 results for “Enet”

Improving evidential deep learning via multi-task learningcs.LG

Enhances ENet's prediction accuracy while maintaining uncertainty estimation.

problem Gradient shrinkage problem in ENet's loss function.

method Proposes a multi-task learning framework with a modified MSE loss function.

result Improves ENet's prediction accuracy without losing uncertainty estimation.

deep learning evidential regression multi-task learning gradient shrinkage uncertainty estimation

2021-12-17abs ↗pdf ↗

SNAP: A semismooth Newton algorithm for pathwise optimization with optimal local convergence rate and oracle propertiesstat.ML

SNAP solves LASSO and Enet efficiently with optimal convergence rates.

problem Sparse, high-dimensional linear regression with LASSO and Enet penalties.

method Semismooth Newton algorithm based on KKT conditions, warm start, and support seeking.

result SNAP converges locally superlinearly for Enet and optimally for LASSO, achieving sharp estimation error bounds.

semismooth Newton pathwise optimization LASSO Enet sparse regression

2018-10-09abs ↗pdf ↗

Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4mlcs.CV

Real-time semantic segmentation for autonomous vehicles on FPGA reduces latency and power consumption.

problem Efficient real-time semantic segmentation for autonomous vehicles.

method Compressed ENet architecture, FPGA deployment, batch processing, filter reduction, quantization-aware training.

result Reduced latency to 3 ms per image with batch size of ten and 40% resource utilization.

FPGAs autonomous vehicles semantic segmentation ENet Cityscapes

2022-05-16abs ↗pdf ↗

FRULER: Fuzzy Rule Learning through Evolution for Regressioncs.LG

In regression problems, the use of TSK fuzzy systems is widely extended due to the precision of the obtained models. Moreover, the use of simple linear TSK models is a good choice in many real problems due to the easy understanding of the relationship between the output and input variables. In this paper we present FRU…

2015-07-17abs ↗pdf ↗