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This work presents a method for adapting a single, fixed deep neural network to multiple tasks without affecting performance on already learned tasks. By building upon ideas from network quantization and pruning, we learn binary masks that…

Computer Vision and Pattern Recognition · Computer Science 2018-03-20 Arun Mallya , Dillon Davis , Svetlana Lazebnik

Persistence diagrams (PDs) are now routinely used to summarize the underlying topology of complex data. Despite several appealing properties, incorporating PDs in learning pipelines can be challenging because their natural geometry is not…

Machine Learning · Statistics 2018-11-14 Théo Lacombe , Marco Cuturi , Steve Oudot

Interval scheduling is a basic problem in the theory of algorithms and a classical task in combinatorial optimization. We develop a set of techniques for partitioning and grouping jobs based on their starting and ending times, that enable…

Data Structures and Algorithms · Computer Science 2023-02-27 Spencer Compton , Slobodan Mitrović , Ronitt Rubinfeld

Conventional LLM inference architectures suffer from high energy and latency due to frequent data movement across memory hierarchies. We propose Ouroboros, a wafer-scale SRAM-based Computing-in-Memory (CIM) architecture that executes all…

Hardware Architecture · Computer Science 2026-03-04 Yiqi Liu , Yudong Pan , Mengdi Wang , Shixin Zhao , Haonan Zhu , Yinhe Han , Lei Zhang , Ying Wang

Binary Neural Network (BNN) represents convolution weights with 1-bit values, which enhances the efficiency of storage and computation. This paper is motivated by a previously revealed phenomenon that the binary kernels in successful BNNs…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Yikai Wang , Wenbing Huang , Yinpeng Dong , Fuchun Sun , Anbang Yao

Second order stationary models in time series analysis are based on the analysis of essential statistics whose computations follow a common pattern. In particular, with a map-reduce nomenclature, most of these operations can be modeled as…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-23 Francois Belletti , Evan Sparks , Michael Franklin , Alexandre M. Bayen

Solving inverse problems with iterative algorithms is popular, especially for large data. Due to time constraints, the number of possible iterations is usually limited, potentially affecting the achievable accuracy. Given an error one is…

Numerical Analysis · Computer Science 2018-02-16 Raja Giryes , Yonina C. Eldar , Alex M. Bronstein , Guillermo Sapiro

Pipeline parallelism has been widely explored, but most existing schedules lack a systematic methodology. In this paper, we propose a framework to decompose pipeline schedules as repeating a building block, and show that the lifespan of the…

Machine Learning · Computer Science 2024-11-05 Penghui Qi , Xinyi Wan , Nyamdavaa Amar , Min Lin

We consider space-bounded computations on a random-access machine (RAM) where the input is given on a read-only random-access medium, the output is to be produced to a write-only sequential-access medium, and the available workspace allows…

Data Structures and Algorithms · Computer Science 2015-10-27 Omar Darwish , Amr Elmasry , Jyrki Katajainen

Both IP lookup and packet classification in IP routers can be implemented by some form of tree traversal. SRAM-based Pipelining can improve the throughput dramatically. However, previous pipelining schemes result in unbalanced memory…

Networking and Internet Architecture · Computer Science 2011-07-28 Weirong Jiang , Hoang Le , Viktor K. Prasanna

In the classical RAM, we have the following useful property. If we have an algorithm that uses $M$ memory cells throughout its execution, and in addition is sparse, in the sense that, at any point in time, only $m$ out of $M$ cells will be…

Quantum Physics · Physics 2022-12-22 Harry Buhrman , Bruno Loff , Subhasree Patro , Florian Speelman

Probability estimation is essential for every statistical data compression algorithm. In practice probability estimation should be adaptive, recent observations should receive a higher weight than older observations. We present a…

Information Theory · Computer Science 2015-01-12 Christopher Mattern

A pebbling move on a graph G consists of the removal of two pebbles from one vertex and the placement of one pebble on an adjacent vertex. Rubbling is a version of pebbling where an additional move is allowed, which is also called the…

Combinatorics · Mathematics 2019-09-05 Zheng-Jiang Xia , Zhen-Mu Hong

The binary indexed tree, or Fenwick tree, is a data structure that can efficiently update values and calculate prefix sums in an array. It allows both of these operations to be performed in $O(\log_2 N)$ time. Here we present a novel data…

Data Structures and Algorithms · Computer Science 2024-03-08 Brent Harrison , Jason Necaise , Andrew Projansky , James D. Whitfield

Network algorithms always prefer low memory cost and fast packet processing speed. Forwarding information base (FIB), as a typical network processing component, requires a scalable and memory-efficient algorithm to support fast lookups. In…

Networking and Internet Architecture · Computer Science 2017-11-23 Ye Yu , Djamal Belazzougui , Chen Qian , Qin Zhang

Important memory-bound kernels, such as linear algebra, convolutions, and stencils, rely on SIMD instructions as well as optimizations targeting improved vectorized data traversal and data re-use to attain satisfactory performance. On on…

Performance · Computer Science 2024-12-23 Miguel O. Blom , Kristian F. D. Rietveld , Rob V. van Nieuwpoort

Short integer linear programs are programs with a relatively small number of constraints. We show how recent improvements on the running-times of solvers for such programs can be used to obtain fast pseudo-polynomial time algorithms for…

Data Structures and Algorithms · Computer Science 2026-02-09 Danny Hermelin , Dvir Shabtay

The problem of space-efficient depth-first search (DFS) is reconsidered. A particularly simple and fast algorithm is presented that, on a directed or undirected input graph $G=(V,E)$ with $n$ vertices and $m$ edges, carries out a DFS in…

Data Structures and Algorithms · Computer Science 2018-05-31 Torben Hagerup

Randomized exponential backoff is a widely deployed technique for coordinating access to a shared resource. A good backoff protocol should, arguably, satisfy three natural properties: (i) it should provide constant throughput, wasting as…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-14 Michael A. Bender , Jeremy T. Fineman , Seth Gilbert , Maxwell Young

Experience replay \citep{lin1993reinforcement, mnih2015human} is a widely used technique to achieve efficient use of data and improved performance in RL algorithms. In experience replay, past transitions are stored in a memory buffer and…

Machine Learning · Computer Science 2021-12-09 Liran Szlak , Ohad Shamir
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