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Yeseong Kim
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2020 – today
- 2024
- [c60]Jungwoo Kim
, Seonggyun Oh
, Jaeha Kung
, Yeseong Kim
, Sungjin Lee
:
NDPipe: Exploiting Near-data Processing for Scalable Inference and Continuous Training in Photo Storage. ASPLOS (3) 2024: 689-707 - [c59]Hyunsei Lee, Hyukjun Kwon, Jiseung Kim, Seohyun Kim, Mohsen Imani, Yeseong Kim:
Towards Forward-Only Learning for Hyperdimensional Computing. DATE 2024: 1-2 - [c58]Hyukjun Kwon, Kangwon Kim, Junyoung Lee, Hyunsei Lee, Jiseung Kim, Jinhyung Kim, Taehyung Kim, Yongnyeon Kim, Yang Ni, Mohsen Imani, Ilhong Suh, Yeseong Kim:
Brain-Inspired Hyperdimensional Computing in the Wild: Lightweight Symbolic Learning for Sensorimotor Controls of Wheeled Robots. ICRA 2024: 5176-5182 - 2023
- [c57]Hyunsei Lee, Jiseung Kim, Hanning Chen, Ariela Zeira, Narayan Srinivasa, Mohsen Imani, Yeseong Kim:
Comprehensive Integration of Hyperdimensional Computing with Deep Learning towards Neuro-Symbolic AI. DAC 2023: 1-6 - [c56]Sanghoon Lee, Jongho Park, Minho Ha, Byungil Koh, Kyoung Park, Yeseong Kim:
Sidekick: Near Data Processing for Clustering Enhanced by Automatic Memory Disaggregation. DAC 2023: 1-6 - [c55]Jiseung Kim, Hyunsei Lee, Mohsen Imani, Yeseong Kim:
Efficient Hyperdimensional Learning with Trainable, Quantizable, and Holistic Data Representation. DATE 2023: 1-6 - [c54]Yang Ni
, Danny Abraham
, Mariam Issa
, Yeseong Kim
, Pietro Mercati
, Mohsen Imani
:
Efficient Off-Policy Reinforcement Learning via Brain-Inspired Computing. ACM Great Lakes Symposium on VLSI 2023: 449-453 - [c53]Mohsen Imani, Yeseong Kim, Behnam Khaleghi, Justin Morris, Haleh Alimohamadi, Farhad Imani, Hugo Latapie:
Hierarchical, Distributed and Brain-Inspired Learning for Internet of Things Systems. ICDCS 2023: 511-522 - [c52]Yang Ni, Yeseong Kim, Tajana Rosing, Mohsen Imani:
Algorithm-Hardware Co-Design for Efficient Brain-Inspired Hyperdimensional Learning on Edge (Extended Abstract). IJCAI 2023: 6474-6479 - [c51]Hanning Chen, Yeseong Kim, Elaheh Sadredini, Saransh Gupta, Hugo Latapie, Mohsen Imani:
Sparsity Controllable Hyperdimensional Computing for Genome Sequence Matching Acceleration. VLSI-SoC 2023: 1-6 - 2022
- [j6]Saransh Gupta
, Mohsen Imani
, Joonseop Sim
, Andrew Huang
, Fan Wu
, Jaeyoung Kang
, Yeseong Kim
, Tajana Simunic Rosing
:
COSMO: Computing with Stochastic Numbers in Memory. ACM J. Emerg. Technol. Comput. Syst. 18(2): 37:1-37:25 (2022) - [j5]Jaeyoung Kang
, Behnam Khaleghi
, Tajana Rosing, Yeseong Kim:
OpenHD: A GPU-Powered Framework for Hyperdimensional Computing. IEEE Trans. Computers 71(11): 2753-2765 (2022) - [c50]Jaeyoung Kang, Behnam Khaleghi, Yeseong Kim, Tajana Rosing:
XCelHD: An Efficient GPU-Powered Hyperdimensional Computing with Parallelized Training. ASP-DAC 2022: 220-225 - [c49]Mohsen Imani, Ali Zakeri, Hanning Chen, Taehyun Kim, Prathyush Poduval, Hyunsei Lee, Yeseong Kim, Elaheh Sadredini
, Farhad Imani:
Neural computation for robust and holographic face detection. DAC 2022: 31-36 - [c48]Prathyush Poduval, Yang Ni, Yeseong Kim, Kai Ni, Raghavan Kumar, Rosario Cammarota, Mohsen Imani:
Adaptive neural recovery for highly robust brain-like representation. DAC 2022: 367-372 - [c47]Jongho Park, Hyukjun Kwon, Seowoo Kim, Junyoung Lee, Minho Ha, Euicheol Lim, Mohsen Imani, Yeseong Kim:
QuiltNet: efficient deep learning inference on multi-chip accelerators using model partitioning. DAC 2022: 1159-1164 - [c46]Yang Ni, Yeseong Kim, Tajana Rosing, Mohsen Imani:
Algorithm-Hardware Co-Design for Efficient Brain-Inspired Hyperdimensional Learning on Edge. DATE 2022: 292-297 - [c45]Yang Ni, Yeseong Kim, Tajana Rosing, Mohsen Imani:
Online Performance and Power Prediction for Edge TPU via Comprehensive Characterization. DATE 2022: 612-615 - [c44]Jun S. Shim, Bogyeong Han, Yeseong Kim, Jihong Kim:
DeepPM: Transformer-based Power and Performance Prediction for Energy-Aware Software. DATE 2022: 1491-1496 - [c43]Jisung Park, Jeonggyun Kim, Yeseong Kim, Sungjin Lee, Onur Mutlu:
DeepSketch: A New Machine Learning-Based Reference Search Technique for Post-Deduplication Delta Compression. FAST 2022: 247-264 - [c42]Zhuowen Zou, Hanning Chen, Prathyush Poduval, Yeseong Kim, Mahdi Imani, Elaheh Sadredini
, Rosario Cammarota, Mohsen Imani:
BioHD: an efficient genome sequence search platform using HyperDimensional memorization. ISCA 2022: 656-669 - [i5]Jisung Park, Jeoggyun Kim, Yeseong Kim, Sungjin Lee, Onur Mutlu:
DeepSketch: A New Machine Learning-Based Reference Search Technique for Post-Deduplication Delta Compression. CoRR abs/2202.10584 (2022) - [i4]Yang Ni, Danny Abraham, Mariam Issa, Yeseong Kim, Pietro Mercati, Mohsen Imani:
QHD: A brain-inspired hyperdimensional reinforcement learning algorithm. CoRR abs/2205.06978 (2022) - 2021
- [j4]Hyeon Gyu Lee
, Minwook Kim, Juwon Lee, Eunji Lee
, Bryan S. Kim
, Sungjin Lee
, Yeseong Kim, Sang Lyul Min, Jin-Soo Kim
:
Learned Performance Model for SSD. IEEE Comput. Archit. Lett. 20(2): 154-157 (2021) - [c41]Yunhui Guo, Mohsen Imani, Jaeyoung Kang
, Sahand Salamat, Justin Morris
, Baris Aksanli
, Yeseong Kim, Tajana Rosing:
HyperRec: Efficient Recommender Systems with Hyperdimensional Computing. ASP-DAC 2021: 384-389 - [c40]Minxuan Zhou, Mohsen Imani, Yeseong Kim, Saransh Gupta, Tajana Rosing:
DP-Sim: A Full-stack Simulation Infrastructure for Digital Processing In-Memory Architectures. ASP-DAC 2021: 639-644 - [c39]Yeseong Kim, Jiseung Kim, Mohsen Imani:
CascadeHD: Efficient Many-Class Learning Framework Using Hyperdimensional Computing. DAC 2021: 775-780 - [c38]Sahand Salamat, Jaeyoung Kang
, Yeseong Kim, Mohsen Imani, Niema Moshiri
, Tajana Rosing:
FPGA Acceleration of Protein Back-Translation and Alignment. DATE 2021: 822-827 - [c37]Zhuowen Zou, Yeseong Kim, M. Hassan Najafi, Mohsen Imani:
ManiHD: Efficient Hyper-Dimensional Learning Using Manifold Trainable Encoder. DATE 2021: 850-855 - [c36]Alejandro Hernández-Cano, Yeseong Kim, Mohsen Imani:
A Framework for Efficient and Binary Clustering in High-Dimensional Space. DATE 2021: 1859-1864 - [c35]Mohsen Imani, Zhuowen Zou, Samuel Bosch, Sanjay Anantha Rao, Sahand Salamat, Venkatesh Kumar, Yeseong Kim, Tajana Rosing:
Revisiting HyperDimensional Learning for FPGA and Low-Power Architectures. HPCA 2021: 221-234 - [c34]Yeseong Kim, Mohsen Imani, Saransh Gupta, Minxuan Zhou, Tajana Simunic Rosing:
Massively Parallel Big Data Classification on a Programmable Processing In-Memory Architecture. ICCAD 2021: 1-9 - [c33]Jiseung Kim, Hyunsei Lee, Mohsen Imani, Yeseong Kim:
Efficient Brain-Inspired Hyperdimensional Learning with Spatiotemporal Structured Data. MASCOTS 2021: 1-8 - [c32]Zhuowen Zou, Yeseong Kim, Farhad Imani, Haleh Alimohamadi, Rosario Cammarota, Mohsen Imani:
Scalable edge-based hyperdimensional learning system with brain-like neural adaptation. SC 2021: 38 - [i3]Zhuowen Zou, Haleh Alimohamadi, Farhad Imani, Yeseong Kim, Mohsen Imani:
Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework. CoRR abs/2110.00214 (2021) - 2020
- [c31]Yeseong Kim, Mohsen Imani, Niema Moshiri
, Tajana Rosing:
GenieHD: Efficient DNA Pattern Matching Accelerator Using Hyperdimensional Computing. DATE 2020: 115-120 - [c30]Mohsen Imani, Mohammad Samragh Razlighi, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar
, Tajana Rosing:
Deep Learning Acceleration with Neuron-to-Memory Transformation. HPCA 2020: 1-14 - [c29]Behnam Khaleghi, Sahand Salamat, Anthony Thomas, Fatemeh Asgarinejad, Yeseong Kim, Tajana Rosing:
SHEARer: highly-efficient hyperdimensional computing by software-hardware enabled multifold approximation. ISLPED 2020: 241-246 - [c28]Mohsen Imani, Saikishan Pampana, Saransh Gupta, Minxuan Zhou, Yeseong Kim, Tajana Rosing:
DUAL: Acceleration of Clustering Algorithms using Digital-based Processing In-Memory. MICRO 2020: 356-371 - [c27]Mohsen Imani, Saransh Gupta, Yeseong Kim, Tajana Rosing:
Deep Learning Acceleration using Digital-Based Processing In-Memory. SoCC 2020: 123-128 - [i2]Behnam Khaleghi, Sahand Salamat, Anthony Thomas, Fatemeh Asgarinejad, Yeseong Kim, Tajana Rosing:
SHEARer: Highly-Efficient Hyperdimensional Computing by Software-Hardware Enabled Multifold Approximation. CoRR abs/2007.10330 (2020)
2010 – 2019
- 2019
- [j3]Yeseong Kim, Mohsen Imani, Tajana Simunic Rosing:
Image Recognition Accelerator Design Using In-Memory Processing. IEEE Micro 39(1): 17-23 (2019) - [c26]Mohsen Imani, Yeseong Kim, M. Sadegh Riazi, John Messerly, Patric Liu, Farinaz Koushanfar
, Tajana Rosing:
A Framework for Collaborative Learning in Secure High-Dimensional Space. CLOUD 2019: 435-446 - [c25]Minxuan Zhou, Mohsen Imani, Saransh Gupta
, Yeseong Kim, Tajana Rosing:
GRAM: graph processing in a ReRAM-based computational memory. ASP-DAC 2019: 591-596 - [c24]Yeseong Kim, Ankit More, Emily Shriver, Tajana Rosing:
Application Performance Prediction and Optimization Under Cache Allocation Technology. DATE 2019: 1285-1288 - [c23]Mohsen Imani, Yeseong Kim, Thomas Worley, Saransh Gupta, Tajana Rosing:
HDCluster: An Accurate Clustering Using Brain-Inspired High-Dimensional Computing. DATE 2019: 1591-1594 - [c22]Joonseop Sim, Saransh Gupta, Mohsen Imani, Yeseong Kim, Tajana Rosing:
UPIM: Unipolar Switching Logic for High Density Processing-in-Memory Applications. ACM Great Lakes Symposium on VLSI 2019: 255-258 - [c21]Mohsen Imani, Saransh Gupta, Yeseong Kim, Minxuan Zhou, Tajana Rosing:
DigitalPIM: Digital-based Processing In-Memory for Big Data Acceleration. ACM Great Lakes Symposium on VLSI 2019: 429-434 - [c20]Anthony Thomas, Yunhui Guo, Yeseong Kim, Baris Aksanli
, Arun Kumar, Tajana Simunic Rosing:
Hierarchical and Distributed Machine Learning Inference Beyond the Edge. ICNSC 2019: 18-23 - [c19]Mohsen Imani, Saransh Gupta, Yeseong Kim, Tajana Rosing:
FloatPIM: in-memory acceleration of deep neural network training with high precision. ISCA 2019: 802-815 - [c18]Dongwon Park, Ilgweon Kang, Yeseong Kim, Sicun Gao, Bill Lin, Chung-Kuan Cheng:
ROAD: Routability Analysis and Diagnosis Framework Based on SAT Techniques. ISPD 2019: 65-72 - [c17]Joonseop Sim, Minsu Kim, Yeseong Kim, Saransh Gupta, Behnam Khaleghi, Tajana Rosing:
MAPIM: Mat Parallelism for High Performance Processing in Non-volatile Memory Architecture. ISQED 2019: 145-150 - [c16]Rishikanth Chandrasekaran, Yunhui Guo, Anthony Thomas, Massimiliano Menarini, Michael H. Ostertag, Yeseong Kim, Tajana Rosing:
Efficient Sparse Processing in Smart Home Applications. SenSys-ML 2019: 19-24 - 2018
- [c15]Yeseong Kim, Mohsen Imani, Tajana Simunic Rosing:
Efficient human activity recognition using hyperdimensional computing. IOT 2018: 38:1-38:6 - [c14]Joonseop Sim, Mohsen Imani, Woojin Choi, Yeseong Kim, Tajana Rosing:
LUPIS: Latch-up based ultra efficient processing in-memory system. ISQED 2018: 55-60 - [i1]Mohsen Imani, Mohammad Samragh, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar, Tajana Rosing:
RAPIDNN: In-Memory Deep Neural Network Acceleration Framework. CoRR abs/1806.05794 (2018) - 2017
- [c13]Mohsen Imani, Yeseong Kim, Tajana Rosing:
MPIM: Multi-purpose in-memory processing using configurable resistive memory. ASP-DAC 2017: 757-763 - [c12]Wanlin Cui, Yeseong Kim, Tajana Simunic Rosing:
Cross-platform machine learning characterization for task allocation in IoT ecosystems. CCWC 2017: 1-7 - [c11]Mohsen Imani, Daniel Peroni, Yeseong Kim, Abbas Rahimi
, Tajana Rosing:
Efficient neural network acceleration on GPGPU using content addressable memory. DATE 2017: 1026-1031 - [c10]Yeseong Kim, Mohsen Imani, Tajana Rosing:
ORCHARD: Visual object recognition accelerator based on approximate in-memory processing. ICCAD 2017: 25-32 - [c9]Yeseong Kim, Pietro Mercati
, Ankit More, Emily Shriver, Tajana Rosing:
P4: Phase-based power/performance prediction of heterogeneous systems via neural networks. ICCAD 2017: 683-690 - [c8]Mohsen Imani, Yeseong Kim, Tajana Rosing:
NNgine: Ultra-Efficient Nearest Neighbor Accelerator Based on In-Memory Computing. ICRC 2017: 1-8 - [c7]Joonseop Sim, Mohsen Imani, Yeseong Kim, Tajana Rosing:
Enabling efficient system design using vertical nanowire transistor current mode logic. VLSI-SoC 2017: 1-6 - 2016
- [j2]Yeseong Kim, Boyeong Jeon, Jihong Kim:
A Personalized Network Activity-Aware Approach to Reducing Radio Energy Consumption of Smartphones. IEEE Trans. Mob. Comput. 15(3): 544-557 (2016) - [c6]Mohsen Imani, Yeseong Kim, Abbas Rahimi
, Tajana Rosing:
ACAM: Approximate Computing Based on Adaptive Associative Memory with Online Learning. ISLPED 2016: 162-167 - [c5]Mohsen Imani, Abbas Rahimi
, Yeseong Kim, Tajana Rosing:
A low-power hybrid magnetic cache architecture exploiting narrow-width values. NVMSA 2016: 1-6 - 2015
- [c4]Yeseong Kim, Francesco Paterna, Sameer Tilak, Tajana Simunic Rosing:
Smartphone Analysis and Optimization based on User Activity Recognition. ICCAD 2015: 605-612 - [c3]Yeseong Kim, Mohsen Imani, Shruti Patil, Tajana Simunic Rosing:
CAUSE: Critical Application Usage-Aware Memory System using Non-volatile Memory for Mobile Devices. ICCAD 2015: 690-696 - [c2]Shruti Patil, Yeseong Kim, Kunal Korgaonkar, Ibrahim Awwal, Tajana Simunic Rosing:
Characterization of User's Behavior Variations for Design of Replayable Mobile Workloads. MobiCASE 2015: 51-70 - 2014
- [j1]Wook Song, Yeseong Kim, Hakbong Kim, Jehun Lim, Jihong Kim:
Personalized optimization for android smartphones. ACM Trans. Embed. Comput. Syst. 13(2s): 60:1-60:25 (2014) - 2012
- [c1]Yeseong Kim, Jihong Kim:
Personalized Diapause: Reducing Radio Energy Consumption of Smartphones by Network-Context Aware Dormancy Predictions. HotPower 2012
Coauthor Index
aka: Tajana Simunic Rosing
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last updated on 2024-08-20 20:31 CEST by the dblp team
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