Milad Hashemi

发表

Continuous runahead: Transparent hardware acceleration for memory intensive workloads

Onur Mutlu, Yale N. Patt, Milad Hashemi, 2016, 2016 49th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

An Imitation Learning Approach for Cache Replacement pdf

Kevin Swersky, Milad Hashemi, Evan Zheran Liu, 2020, ICML.

Data-Driven Offline Optimization For Architecting Hardware Accelerators pdf

Sergey Levine, Aviral Kumar, Kevin Swersky, 2021, ArXiv.

Reducing Memory Access Latency via an Enhanced ( Compute Capable ) Memory Controller

Khubaib, O. Mutlu, Y. Patt, 2015 .

Apollo: Transferable Architecture Exploration

Amir Yazdanbakhsh, Kevin Swersky, Milad Hashemi, 2021, ArXiv.

First geoarchaeological study of a Palaeolithic site on the northern edge of the Iranian Central Desert: Mirak (Semnan, Iran)

Milad Hashemi, G. Guérin, P. Antoine, 2022, Journal of Arid Environments.

Do Bayesian methods lead to more precise chronologies? ‘BayLum’ and a first OSL-based chronology for the Palaeolithic open-air site of Mirak (Iran)

Milad Hashemi, G. Guérin, Maryam Heydari, 2020, Quaternary Geochronology.

The open-air Paleolithic site of Mirak, northern edge of the Iranian Central Desert (Semnan, Iran): Evidence of repeated human occupations during the late Pleistocene

Milad Hashemi, G. Guérin, S. Puaud, 2019, Comptes Rendus Palevol.

Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks

Kevin Swersky, Milad Hashemi, Danai Koutra, 2021, ArXiv.

Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks

Thomas Kipf, Kevin Swersky, Renjie Liao, 2022, ArXiv.

Playas and Middle Paleolithic settlement of the Iranian Central Desert: The discovery of the Chah-e Jam Middle Paleolithic site

Milad Hashemi, H. V. Nasab, 2016 .

Learning Memory Access Patterns pdf

Christoforos E. Kozyrakis, Jichuan Chang, Parthasarathy Ranganathan, 2018, ICML.

No MCMC for me: Amortized sampling for fast and stable training of energy-based models

D. Duvenaud, Will Grathwohl, Mohammad Norouzi, 2020, ICLR.

Data-Driven Offline Optimization For Architecting Hardware Accelerators

S. Levine, Aviral Kumar, Kevin Swersky, 2021, ICLR.

Oops I Took A Gradient: Scalable Sampling for Discrete Distributions pdf

David Duvenaud, Chris J. Maddison, Kevin Swersky, 2021, ICML.

Learning Performance-Improving Code Edits

Graham Neubig, Milad Hashemi, Aman Madaan, 2023, ArXiv.

Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks

Kevin Swersky, Milad Hashemi, Danai Koutra, 2021, 2022 IEEE International Conference on Data Mining (ICDM).

Neural Execution Engines: Learning to Execute Subroutines

Kevin Swersky, Milad Hashemi, Danai Koutra, 2020, NeurIPS.

Learning Execution through Neural Code Fusion pdf

Daniel Tarlow, Zhan Shi, Kevin Swersky, 2019, ICLR.

NEURAL EXECUTION ENGINES

Danai Koutra, Kevin Swersky, Milad Hashemi, 2019 .

Accelerating Dependent Cache Misses with an Enhanced Memory Controller

Onur Mutlu, Yale N. Patt, Milad Hashemi, 2016, 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA).

A hierarchical neural model of data prefetching

Parthasarathy Ranganathan, Calvin Lin, Akanksha Jain, 2021, ASPLOS.

Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks

Thomas Kipf, Kevin Swersky, Renjie Liao, 2022, Trans. Mach. Learn. Res..

Learned Hardware/Software Co-Design of Neural Accelerators pdf

Calvin Lin, Kevin Swersky, Milad Hashemi, 2020, ArXiv.

CUF: Continuous Upsampling Filters

Kevin Swersky, Milad Hashemi, A. Tagliasacchi, 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Filtered runahead execution with a runahead buffer

Yale N. Patt, Milad Hashemi, Y. Patt, 2015, 2015 48th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

On-Chip Mechanisms to Reduce Effective Memory Access Latency pdf

Milad Hashemi, Milad Hashemi, 2016, ArXiv.

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

I. G. Ampomah, Amir Mehdi Shayan, Sathish Kumar Jayapal, 2024, The Lancet.

Using Bayesian Optimization for Hardware/Software Co-Design of Neural Accelerators

Kevin Swersky, Milad Hashemi, Zhan Shi, 2020 .

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Mohammad Hosein Amirzade-Iranaq, Duc Tran Minh, Fahad Mashhour Alanezi, 2024, The Lancet.

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Myron Anthony Godinho, Sathish Kumar Jayapal, D. P. Rasali, 2024, The Lancet.

Temporal patterns of cancer burden in Asia, 1990–2019: a systematic examination for the Global Burden of Disease 2019 study

Vijay Kumar Chattu, Fahad Mashhour Alanezi, M. Naghavi, 2024, The Lancet regional health. Southeast Asia.