
LearningBased Distributed Random Access for MultiCell IoT Networks with NOMA
Nonorthogonal multiple access (NOMA) is a key technology to enable mass...
read it

AgEBOTabular: Joint Neural Architecture and Hyperparameter Search with Autotuned DataParallel Training for Tabular Data
Developing highperforming predictive models for large tabular data sets...
read it

Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization
An autotuning is an approach that explores a search space of possible im...
read it

Dynamic Graph Neural Network for Traffic Forecasting in Wide Area Networks
Wide area networking infrastructures (WANs), particularly science and re...
read it

Graph Neural Network Architecture Search for Molecular Property Prediction
Predicting the properties of a molecule from its structure is a challeng...
read it

Meta Continual Learning via Dynamic Programming
Metacontinual learning algorithms seek to rapidly train a model when fa...
read it

Multilayer Neuromodulated Architectures for MemoryConstrained Online Continual Learning
We focus on the problem of how to achieve online continual learning unde...
read it

A GradientAware Search Algorithm for Constrained Markov Decision Processes
The canonical solution methodology for finite constrained Markov decisio...
read it

Towards OnChip Bayesian Neuromorphic Learning
If edge devices are to be deployed to critical applications where their ...
read it

Transfer Learning with Graph Neural Networks for ShortTerm Highway Traffic Forecasting
Highway traffic modeling and forecasting approaches are critical for int...
read it

Constrained Deep Reinforcement Learning for Energy Sustainable MultiUAV based Random Access IoT Networks with NOMA
In this paper, we apply the NonOrthogonal Multiple Access (NOMA) techni...
read it

Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems
Quantum computing is a computational paradigm with the potential to outp...
read it

ReinforcementLearningBased Variational Quantum Circuits Optimization for Combinatorial Problems
Quantum computing exploits basic quantum phenomena such as state superpo...
read it

ValueAdded Chemical Discovery Using Reinforcement Learning
Computerassisted synthesis planning aims to help chemists find better r...
read it

Modular Deep Learning Analysis of GalaxyScale Strong Lensing Images
Strong gravitational lensing of astrophysical sources by foreground gala...
read it

GraphPartitioningBased Diffusion Convolution Recurrent Neural Network for LargeScale Traffic Forecasting
Traffic forecasting approaches are critical to developing adaptive strat...
read it

MaLTESE: LargeScale SimulationDriven Machine Learning for Transient Driving Cycles
Optimal engine operation during a transient driving cycle is the key to ...
read it

Using recurrent neural networks for nonlinear component computation in advectiondominated reducedorder models
Rapid simulations of advectiondominated problems are vital for multiple...
read it

Balsam: Automated Scheduling and Execution of Dynamic, DataIntensive HPC Workflows
We introduce the Balsam service to manage highthroughput task schedulin...
read it

Scalable ReinforcementLearningBased Neural Architecture Search for Cancer Deep Learning Research
Cancer is a complex disease, the understanding and treatment of which ar...
read it

Neuromorphic Architecture Optimization for TaskSpecific Dynamic Learning
The ability to learn and adapt in real time is a central feature of biol...
read it

Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout
As neural networks have begun performing increasingly critical tasks for...
read it
Prasanna Balaprakash
is this you? claim profile