Aleksandar Zlateski

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 17

Top Venues

CoRR

PPOPP

ICS

CVC (1)

Massachusetts Institute of Technology, Cambridge, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, USA

PHD

Publications

George Mitenkov, Igor Kabiljo, Zekun Li, Alexander Spiegelman, Satyanarayana Vusirikala, Zhuolun Xiang, Aleksandar Zlateski, Nuno P. Lopes, Rati Gelashvili
Deferred Objects to Enhance Smart Contract Programming with Optimistic Parallel Execution. CoRR (2024)
Dejan Grubisic, Bram Wasti, Chris Cummins, John M. Mellor-Crummey, Aleksandar Zlateski
LoopTune: Optimizing Tensor Computations with Reinforcement Learning. CoRR (2023)
Bram Wasti, José Pablo Cambronero, Benoit Steiner, Hugh Leather, Aleksandar Zlateski
LoopStack: a Lightweight Tensor Algebra Compiler Stack. CoRR (2022)
Ran Lu, Aleksandar Zlateski, H. Sebastian Seung
Large-scale image segmentation based on distributed clustering algorithms. CoRR (2021)
Sergiy Popovych, Davit Buniatyan, Aleksandar Zlateski, Kai Li, H. Sebastian Seung
PZnet: Efficient 3D ConvNet Inference on Manycore CPUs. CVC (1) (2019)
Rati Gelashvili, Nir Shavit, Aleksandar Zlateski
L3 Fusion: Fast Transformed Convolutions on CPUs. CoRR (2019)
Aleksandar Zlateski, Zhen Jia, Kai Li, Frédo Durand
The anatomy of efficient FFT and winograd convolutions on modern CPUs. ICS (2019)
Sergiy Popovych, Davit Buniatyan, Aleksandar Zlateski, Kai Li, H. Sebastian Seung
PZnet: Efficient 3D ConvNet Inference on Manycore CPUs. CoRR (2019)
Zhen Jia, Aleksandar Zlateski, Frédo Durand, Kai Li
Optimizing N-dimensional, winograd-based convolution for manycore CPUs. PPOPP (2018)
Aleksandar Zlateski, Zhen Jia, Kai Li, Frédo Durand
FFT Convolutions are Faster than Winograd on Modern CPUs, Here is Why. CoRR (2018)
Aleksandar Zlateski, Ronnachai Jaroensri, Prafull Sharma, Frédo Durand
On the Importance of Label Quality for Semantic Segmentation. CVPR (2018)
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
Scalable training of 3D convolutional networks on multi- and many-cores. J. Parallel Distributed Comput. 106 (2017)
Alexander Matveev, Yaron Meirovitch, Hayk Saribekyan, Wiktor Jakubiuk, Tim Kaler, Gergely Ódor, David M. Budden, Aleksandar Zlateski, Nir Shavit
A Multicore Path to Connectomics-on-Demand. PPOPP (2017)
Aleksandar Zlateski, H. Sebastian Seung
Compile-time optimized and statically scheduled N-D convnet primitives for multi-core and many-core (Xeon Phi) CPUs. ICS (2017)
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
ZNNi - Maximizing the Inference Throughput of 3D Convolutional Networks on Multi-Core CPUs and GPUs. CoRR (2016)
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
ZNN - A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-core and Many-Core Shared Memory Machines. IPDPS (2016)
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
: maximizing the inference throughput of 3D convolutional networks on CPUs and GPUs. SC (2016)
Kisuk Lee, Aleksandar Zlateski, Ashwin Vishwanathan, H. Sebastian Seung
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Prediction. NIPS (2015)
Aleksandar Zlateski, H. Sebastian Seung
Image Segmentation by Size-Dependent Single Linkage Clustering of a Watershed Basin Graph. CoRR (2015)
Kisuk Lee, Aleksandar Zlateski, Ashwin Vishwanathan, H. Sebastian Seung
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Detection. CoRR (2015)
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
ZNN - A Fast and Scalable Algorithm for Training 3D Convolutional Networks on Multi-Core and Many-Core Shared Memory Machines. CoRR (2015)

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Publication Activity (10 Years)

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Aleksandar Zlateski