Aleksandar Zlateski

According to our database, Aleksandar Zlateski authored at least 19 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

LoopTune: Optimizing Tensor Computations with Reinforcement Learning.

Dejan Grubisic, Bram Wasti, Chris Cummins, John M. Mellor-Crummey, Aleksandar Zlateski

CoRR, 2023

2022

LoopStack: a Lightweight Tensor Algebra Compiler Stack.

Bram Wasti, José Pablo Cambronero, Benoit Steiner, Hugh Leather, Aleksandar Zlateski

CoRR, 2022

2021

Large-scale image segmentation based on distributed clustering algorithms.

Ran Lu, Aleksandar Zlateski, H. Sebastian Seung

CoRR, 2021

2019

L3 Fusion: Fast Transformed Convolutions on CPUs.

Rati Gelashvili, Nir Shavit, Aleksandar Zlateski

CoRR, 2019

The anatomy of efficient FFT and winograd convolutions on modern CPUs.

Aleksandar Zlateski, Zhen Jia, Kai Li, Frédo Durand

Proceedings of the ACM International Conference on Supercomputing, 2019

PZnet: Efficient 3D ConvNet Inference on Manycore CPUs.

Sergiy Popovych, Davit Buniatyan, Aleksandar Zlateski, Kai Li, H. Sebastian Seung

Proceedings of the Advances in Computer Vision, 2019

2018

FFT Convolutions are Faster than Winograd on Modern CPUs, Here is Why.

Aleksandar Zlateski, Zhen Jia, Kai Li, Frédo Durand

CoRR, 2018

Optimizing N-dimensional, winograd-based convolution for manycore CPUs.

Zhen Jia, Aleksandar Zlateski, Frédo Durand, Kai Li

Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2018

On the Importance of Label Quality for Semantic Segmentation.

Aleksandar Zlateski, Ronnachai Jaroensri, Prafull Sharma, Frédo Durand

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Scalable training of 3D convolutional networks on multi- and many-cores.

Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung

J. Parallel Distributed Comput., 2017

A Multicore Path to Connectomics-on-Demand.

Alexander Matveev, Yaron Meirovitch, Hayk Saribekyan, Wiktor Jakubiuk, Tim Kaler, Gergely Ódor, David M. Budden, Aleksandar Zlateski, Nir Shavit

Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2017

Compile-time optimized and statically scheduled N-D convnet primitives for multi-core and many-core (Xeon Phi) CPUs.

Aleksandar Zlateski, H. Sebastian Seung

Proceedings of the International Conference on Supercomputing, 2017

2016

Scalable algorithms for semi-automatic segmentation of electron microscopy images of the brain tissue.

Aleksandar Zlateski

PhD thesis, 2016

ZNNi - Maximizing the Inference Throughput of 3D Convolutional Networks on Multi-Core CPUs and GPUs.

Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung

CoRR, 2016

ZNN<i>i</i>: maximizing the inference throughput of 3D convolutional networks on CPUs and GPUs.

Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung

Proceedings of the International Conference for High Performance Computing, 2016

ZNN - A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-core and Many-Core Shared Memory Machines.

Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium, 2016

2015

Image Segmentation by Size-Dependent Single Linkage Clustering of a Watershed Basin Graph.

Aleksandar Zlateski, H. Sebastian Seung

CoRR, 2015

Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Detection.

Kisuk Lee, Aleksandar Zlateski, Ashwin Vishwanathan, H. Sebastian Seung

CoRR, 2015

Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Prediction.

Kisuk Lee, Aleksandar Zlateski, Ashwin Vishwanathan, H. Sebastian Seung

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015