Stylianos I. Venieris

95 papers A* 11A 6B 6C 2Misc 4Journal 57Unranked 8
YearRankTypeTitle / Venue / Authors
2026 A* conf
FedP²EFT: Federated Learning to Personalize PEFT for Multilingual LLMs.
AAAI
Royson Lee, Minyoung Kim, Fady Rezk, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales
2026 A* conf
HierarchicalPrune: Position-Aware Compression for Large-Scale Diffusion Models.
AAAI
Young D. Kwon, Rui Li, Sijia Li, Da Li, Sourav Bhattacharya, Stylianos I. Venieris
2026 J jnl
Speculative Decoding with a Speculative Vocabulary.
CoRR
Miles Williams, Young D. Kwon, Rui Li, Alexandros Kouris, Stylianos I. Venieris
2025 J jnl
Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT.
CoRR
Ioannis Panopoulos, Maria-Lamprini A. Bartsioka, Sokratis Nikolaidis, Stylianos I. Venieris, Dimitra I. Kaklamani, Iakovos S. Venieris
2025 J jnl
FedP
CoRR
Royson Lee, Minyoung Kim, Fady Rezk, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales
2025 — conf
Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference.
EMNLP (Findings)
Hao Mark Chen, Wayne Luk, Yiu Ka Fai Cedric, Rui Li, Konstantin Mishchenko, Stylianos I. Venieris, Hongxiang Fan
2025 J jnl
HierarchicalPrune: Position-Aware Compression for Large-Scale Diffusion Models.
CoRR
Young D. Kwon, Rui Li, Sijia Li, Da Li, Sourav Bhattacharya, Stylianos I. Venieris
2025 A* conf
Progressive Mixed-Precision Decoding for Efficient LLM Inference.
ICLR
Hao Mark Chen, Fuwen Tan, Alexandros Kouris, Royson Lee, Hongxiang Fan, Stylianos I. Venieris
2024 J jnl
CARIn: Constraint-Aware and Responsive Inference on Heterogeneous Devices for Single- and Multi-DNN Workloads.
CoRR
Ioannis Panopoulos, Stylianos I. Venieris, Iakovos S. Venieris
2024 J jnl
CARIn: Constraint-Aware and Responsive Inference on Heterogeneous Devices for Single- and Multi-DNN Workloads.
ACM Trans. Embed. Comput. Syst.
Ioannis Panopoulos, Stylianos I. Venieris, Iakovos S. Venieris
2024 J jnl
Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference.
CoRR
Hao Mark Chen, Wayne Luk, Ka Fai Cedric Yiu, Rui Li, Konstantin Mishchenko, Stylianos I. Venieris, Hongxiang Fan
2024 A conf
Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation.
WACV
Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
2024 J jnl
MultiTASC++: A Continuously Adaptive Scheduler for Edge-Based Multi-Device Cascade Inference.
CoRR
Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris
2024 J jnl
NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution.
IEEE Trans. Mob. Comput.
Stylianos I. Venieris, Mário Almeida, Royson Lee, Nicholas D. Lane
2024 J jnl
Progressive Mixed-Precision Decoding for Efficient LLM Inference.
CoRR
Hao Mark Chen, Fuwen Tan, Alexandros Kouris, Royson Lee, Hongxiang Fan, Stylianos I. Venieris
2024 J jnl
The Future of Consumer Edge-AI Computing.
IEEE Pervasive Comput.
Stefanos Laskaridis, Stylianos I. Venieris, Alexandros Kouris, Rui Li, Nicholas D. Lane
2024 A* conf
TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge.
ICML
Young D. Kwon, Rui Li, Stylianos I. Venieris, Jagmohan Chauhan, Nicholas Donald Lane, Cecilia Mascolo
2023 C conf
Exploring the Performance and Efficiency of Transformer Models for NLP on Mobile Devices.
ISCC
Ioannis Panopoulos, Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris
2023 J jnl
Exploring the Performance and Efficiency of Transformer Models for NLP on Mobile Devices.
CoRR
Ioannis Panopoulos, Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris
2023 Misc conf
LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms.
SenSys
Young D. Kwon, Jagmohan Chauhan, Hong Jia, Stylianos I. Venieris, Cecilia Mascolo
2023 J jnl
LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms.
CoRR
Young D. Kwon, Jagmohan Chauhan, Hong Jia, Stylianos I. Venieris, Cecilia Mascolo
2023 J jnl
Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation.
CoRR
Stylianos I. Venieris, Javier Fernández-Marqués, Nicholas D. Lane
2023 J jnl
Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation.
ACM Trans. Design Autom. Electr. Syst.
Stylianos I. Venieris, Javier Fernández-Marqués, Nicholas D. Lane
2023 C conf
MultiTASC: A Multi-Tenancy-Aware Scheduler for Cascaded DNN Inference at the Consumer Edge.
ISCC
Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris
2023 J jnl
MultiTASC: A Multi-Tenancy-Aware Scheduler for Cascaded DNN Inference at the Consumer Edge.
CoRR
Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris
2023 J jnl
Multiple-Deep Neural Network Accelerators for Next-Generation Artificial Intelligence Systems.
Computer
Stylianos I. Venieris, Christos-Savvas Bouganis, Nicholas D. Lane
2023 A* conf
Sparse-DySta: Sparsity-Aware Dynamic and Static Scheduling for Sparse Multi-DNN Workloads.
MICRO
Hongxiang Fan, Stylianos I. Venieris, Alexandros Kouris, Nicholas D. Lane
2023 J jnl
Sparse-DySta: Sparsity-Aware Dynamic and Static Scheduling for Sparse Multi-DNN Workloads.
CoRR
Hongxiang Fan, Stylianos I. Venieris, Alexandros Kouris, Nicholas D. Lane
2023 J jnl
TinyTrain: Deep Neural Network Training at the Extreme Edge.
CoRR
Young D. Kwon, Rui Li, Stylianos I. Venieris, Jagmohan Chauhan, Nicholas D. Lane, Cecilia Mascolo
2022 A* conf
Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design.
MICRO
Hongxiang Fan, Thomas Chau, Stylianos I. Venieris, Royson Lee, Alexandros Kouris, Wayne Luk, Nicholas D. Lane, Mohamed S. Abdelfattah
2022 J jnl
Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design.
CoRR
Hongxiang Fan, Thomas Chun-Pong Chau, Stylianos I. Venieris, Royson Lee, Alexandros Kouris, Wayne Luk, Nicholas D. Lane, Mohamed S. Abdelfattah
2022 A conf
Adaptable mobile vision systems through multi-exit neural networks.
MobiSys
Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane
2022 J jnl
Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions.
ACM Comput. Surv.
Royson Lee, Stylianos I. Venieris, Nicholas D. Lane
2022 J jnl
DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device.
ACM Trans. Embed. Comput. Syst.
Mário Almeida, Stefanos Laskaridis, Stylianos I. Venieris, Ilias Leontiadis, Nicholas D. Lane
2022 J jnl
Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs.
CoRR
Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane
2022 J jnl
Guest Editorial: Bridging the Gap Between Industry and Academia for Networking Research.
IEEE Netw.
Bo Han, Jiasi Chen, Tian Guo, Sung-Ju Lee, Viswanathan Swaminathan, Stylianos I. Venieris
2022 J jnl
Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation.
CoRR
Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
2022 J jnl
Multi-DNN Accelerators for Next-Generation AI Systems.
CoRR
Stylianos I. Venieris, Christos-Savvas Bouganis, Nicholas D. Lane
2022 — conf
Multi-Exit Semantic Segmentation Networks.
ECCV (21)
Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane
2022 J jnl
NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution.
CoRR
Stylianos I. Venieris, Mário Almeida, Royson Lee, Nicholas D. Lane
2022 J jnl
The Future of Consumer Edge-AI Computing.
CoRR
Stefanos Laskaridis, Stylianos I. Venieris, Alexandros Kouris, Rui Li, Nicholas D. Lane
2021 J jnl
Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions.
CoRR
Royson Lee, Stylianos I. Venieris, Nicholas D. Lane
2021 J jnl
DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device.
CoRR
Mário Almeida, Stefanos Laskaridis, Stylianos I. Venieris, Ilias Leontiadis, Nicholas D. Lane
2021 A* conf
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout.
NeurIPS
Samuel Horváth, Stefanos Laskaridis, Mário Almeida, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane
2021 J jnl
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout.
CoRR
Samuel Horváth, Stefanos Laskaridis, Mário Almeida, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane
2021 — conf
How to Reach Real-Time AI on Consumer Devices? Solutions for Programmable and Custom Architectures.
ASAP
Stylianos I. Venieris, Ioannis Panopoulos, Ilias Leontiadis, Iakovos S. Venieris
2021 J jnl
How to Reach Real-Time AI on Consumer Devices? Solutions for Programmable and Custom Architectures.
CoRR
Stylianos I. Venieris, Ioannis Panopoulos, Ilias Leontiadis, Iakovos S. Venieris
2021 Misc conf
It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation.
HotMobile
Ilias Leontiadis, Stefanos Laskaridis, Stylianos I. Venieris, Nicholas D. Lane
2021 J jnl
It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation.
CoRR
Ilias Leontiadis, Stefanos Laskaridis, Stylianos I. Venieris, Nicholas D. Lane
2021 J jnl
Multi-Exit Semantic Segmentation Networks.
CoRR
Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane
2021 B conf
OODIn: An Optimised On-Device Inference Framework for Heterogeneous Mobile Devices.
SMARTCOMP
Stylianos I. Venieris, Ioannis Panopoulos, Iakovos S. Venieris
2021 J jnl
OODIn: An Optimised On-Device Inference Framework for Heterogeneous Mobile Devices.
CoRR
Stylianos I. Venieris, Ioannis Panopoulos, Iakovos S. Venieris
2021 Misc conf
unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation.
FCCM
Stylianos I. Venieris, Javier Fernández-Marqués, Nicholas D. Lane
2021 J jnl
unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation.
CoRR
Stylianos I. Venieris, Javier Fernández-Marqués, Nicholas D. Lane
2020 A conf
A Throughput-Latency Co-Optimised Cascade of Convolutional Neural Network Classifiers.
DATE
Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis
2020 J jnl
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars.
IEEE Consumer Electron. Mag.
Alexandros Kouris, Stylianos I. Venieris, Michail Rizakis, Christos-Savvas Bouganis
2020 B conf
Caffe Barista: Brewing Caffe with FPGAs in the Training Loop.
FPL
Diederik Adriaan Vink, Aditya Rajagopal, Stylianos I. Venieris, Christos-Savvas Bouganis
2020 J jnl
Caffe Barista: Brewing Caffe with FPGAs in the Training Loop.
CoRR
Diederik Adriaan Vink, Aditya Rajagopal, Stylianos I. Venieris, Christos-Savvas Bouganis
2020 J jnl
Countering Acoustic Adversarial Attacks in Microphone-equipped Smart Home Devices.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.
Sourav Bhattacharya, Dionysis Manousakas, Alberto Gil C. P. Ramos, Stylianos I. Venieris, Nicholas D. Lane, Cecilia Mascolo
2020 A conf
HAPI: Hardware-Aware Progressive Inference.
ICCAD
Stefanos Laskaridis, Stylianos I. Venieris, Hyeji Kim, Nicholas D. Lane
2020 J jnl
HAPI: Hardware-Aware Progressive Inference.
CoRR
Stefanos Laskaridis, Stylianos I. Venieris, Hyeji Kim, Nicholas D. Lane
2020 — conf
Journey Towards Tiny Perceptual Super-Resolution.
ECCV (26)
Royson Lee, Lukasz Dudziak, Mohamed S. Abdelfattah, Stylianos I. Venieris, Hyeji Kim, Hongkai Wen, Nicholas D. Lane
2020 J jnl
Journey Towards Tiny Perceptual Super-Resolution.
CoRR
Royson Lee, Lukasz Dudziak, Mohamed S. Abdelfattah, Stylianos I. Venieris, Hyeji Kim, Hongkai Wen, Nicholas D. Lane
2020 A* conf
Multi-Precision Policy Enforced Training (MuPPET) : A Precision-Switching Strategy for Quantised Fixed-Point Training of CNNs.
ICML
Aditya Rajagopal, Diederik Adriaan Vink, Stylianos I. Venieris, Christos-Savvas Bouganis
2020 J jnl
Multi-Precision Policy Enforced Training (MuPPET): A precision-switching strategy for quantised fixed-point training of CNNs.
CoRR
Aditya Rajagopal, Diederik Adriaan Vink, Stylianos I. Venieris, Christos-Savvas Bouganis
2020 — conf
Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions.
DistributedML@CoNEXT
Royson Lee, Stylianos I. Venieris, Nicholas D. Lane
2020 J jnl
Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions.
CoRR
Royson Lee, Stylianos I. Venieris, Nicholas D. Lane
2020 J jnl
SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud.
CoRR
Stefanos Laskaridis, Stylianos I. Venieris, Mário Almeida, Ilias Leontiadis, Nicholas D. Lane
2020 A* conf
SPINN: synergistic progressive inference of neural networks over device and cloud.
MobiCom
Stefanos Laskaridis, Stylianos I. Venieris, Mário Almeida, Ilias Leontiadis, Nicholas D. Lane
2019 J jnl
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars.
CoRR
Alexandros Kouris, Stylianos I. Venieris, Michail Rizakis, Christos-Savvas Bouganis
2019 — —
Automated methodologies for mapping convolutional neural networks on reconfigurable hardware.
Stylianos I. Venieris
2019 J jnl
EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices.
CoRR
Mário Almeida, Stefanos Laskaridis, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane
2019 A* conf
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors.
MobiCom
Royson Lee, Stylianos I. Venieris, Lukasz Dudziak, Sourav Bhattacharya, Nicholas D. Lane
2019 J jnl
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors.
CoRR
Royson Lee, Stylianos I. Venieris, Lukasz Dudziak, Sourav Bhattacharya, Nicholas D. Lane
2019 A* conf
Poster: MobiSR - Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors.
MobiCom
Royson Lee, Stylianos I. Venieris, Lukasz Dudziak, Sourav Bhattacharya, Nicholas D. Lane
2019 — conf
Power-Aware FPGA Mapping of Convolutional Neural Networks.
FPT
Alexander Montgomerie-Corcoran, Stylianos I. Venieris, Christos-Savvas Bouganis
2019 — conf
Towards Efficient On-Board Deployment of DNNs on Intelligent Autonomous Systems.
ISVLSI
Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis
2019 J jnl
fpgaConvNet: Mapping Regular and Irregular Convolutional Neural Networks on FPGAs.
IEEE Trans. Neural Networks Learn. Syst.
Stylianos I. Venieris, Christos-Savvas Bouganis
2018 — conf
Approximate FPGA-Based LSTMs Under Computation Time Constraints.
ARC
Michalis Rizakis, Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis
2018 J jnl
Approximate FPGA-based LSTMs under Computation Time Constraints.
CoRR
Michalis Rizakis, Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis
2018 J jnl
CascadeCNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks.
CoRR
Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis
2018 J jnl
CascadeCNN: Pushing the performance limits of quantisation.
CoRR
Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis
2018 B conf
Cascade^CNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks.
FPL
Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis
2018 J jnl
Deploying Deep Neural Networks in the Embedded Space.
CoRR
Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis
2018 A conf
DroNet: Efficient convolutional neural network detector for real-time UAV applications.
DATE
Christos Kyrkou, George Plastiras, Theocharis Theocharides, Stylianos I. Venieris, Christos-Savvas Bouganis
2018 J jnl
DroNet: Efficient convolutional neural network detector for real-time UAV applications.
CoRR
Christos Kyrkou, George Plastiras, Stylianos I. Venieris, Theocharis Theocharides, Christos-Savvas Bouganis
2018 J jnl
Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions.
CoRR
Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis
2018 J jnl
Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions.
ACM Comput. Surv.
Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis
2018 J jnl
f-CNN
CoRR
Stylianos I. Venieris, Christos-Savvas Bouganis
2018 B conf
f-CNNx: A Toolflow for Mapping Multiple Convolutional Neural Networks on FPGAs.
FPL
Stylianos I. Venieris, Christos-Savvas Bouganis
2017 B conf
Latency-driven design for FPGA-based convolutional neural networks.
FPL
Stylianos I. Venieris, Christos-Savvas Bouganis
2017 J jnl
fpgaConvNet: A Toolflow for Mapping Diverse Convolutional Neural Networks on Embedded FPGAs.
CoRR
Stylianos I. Venieris, Christos-Savvas Bouganis
2017 A conf
fpgaConvNet: Automated Mapping of Convolutional Neural Networks on FPGAs (Abstract Only).
FPGA
Stylianos I. Venieris, Christos-Savvas Bouganis
2016 Misc conf
fpgaConvNet: A Framework for Mapping Convolutional Neural Networks on FPGAs.
FCCM
Stylianos I. Venieris, Christos-Savvas Bouganis
2015 B conf
Towards heterogeneous solvers for large-scale linear systems.
FPL
Stylianos I. Venieris, Grigorios Mingas, Christos-Savvas Bouganis