Aleksandar Zlateski

22 papers A* 1A 4B 2Journal 12Unranked 2

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