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02/16/2023
THC: Accelerating Distributed Deep Learning Using Tensor Homomorphic Compression
Deep neural networks (DNNs) are the de-facto standard for essential use ...
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11/03/2022
SQUID: Faster Analytics via Sampled Quantiles Data-structure
Measurement is a fundamental enabler of network applications such as loa...
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08/09/2022
Enabling Efficient and General Subpopulation Analytics in Multidimensional Data Streams
Today's large-scale services (e.g., video streaming platforms, data cent...
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05/26/2022
QUIC-FL: Quick Unbiased Compression for Federated Learning
Distributed Mean Estimation (DME) is a fundamental building block in com...
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04/29/2022
FRANCIS: Fast Reaction Algorithms for Network Coordination In Switches
Distributed protocols are widely used to support network functions such ...
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02/04/2022
Direct Telemetry Access
The emergence of programmable switches allows operators to collect a vas...
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01/06/2022
SQUAD: Combining Sketching and Sampling Is Better than Either for Per-item Quantile Estimation
Stream monitoring is fundamental in many data stream applications, such ...
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10/11/2021
Zero-CPU Collection with Direct Telemetry Access
Programmable switches are driving a massive increase in fine-grained mea...
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08/19/2021
Communication-Efficient Federated Learning via Robust Distributed Mean Estimation
Federated learning commonly relies on algorithms such as distributed (mi...
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05/18/2021
DRIVE: One-bit Distributed Mean Estimation
We consider the problem where n clients transmit d-dimensional real-valu...
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02/24/2021
SALSA: Self-Adjusting Lean Streaming Analytics
Counters are the fundamental building block of many data sketching schem...
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10/05/2020
How to send a real number using a single bit (and some shared randomness)
We consider the fundamental problem of communicating an estimate of a re...
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07/07/2020
PINT: Probabilistic In-band Network Telemetry
Commodity network devices support adding in-band telemetry measurements ...
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04/21/2020
Faster and More Accurate Measurement through Additive-Error Counters
Counters are a fundamental building block for networking applications su...
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04/10/2020
Cheetah: Accelerating Database Queries with Switch Pruning
Modern database systems are growing increasingly distributed and struggl...
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02/25/2019
Optimal Distributed Covering Algorithms
We present a time-optimal deterministic distributed algorithm for approx...
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10/05/2018
Memento: Making Sliding Windows Efficient for Heavy Hitters
Cloud operators require real-time identification of Heavy Hitters (HH) a...
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09/14/2018
Approximate Query Processing over Static Sets and Sliding Windows
Indexing of static and dynamic sets is fundamental to a large set of app...
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08/17/2018
Optimal Distributed Weighted Set Cover Approximation
We present a time-optimal deterministic distributed algorithm for approx...
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08/10/2018
Efficient Measurement on Programmable Switches Using Probabilistic Recirculation
Programmable network switches promise flexibility and high throughput, e...
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08/10/2018
Efficient Measurement on Programmable SwitchesUsing Probabilistic Recirculation
Programmable network switches promise flexibility and high throughput, e...
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07/13/2018
Parameterized Distributed Algorithms
In this work, we initiate a thorough study of parameterized graph optimi...
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04/28/2018
Heavy Hitters over Interval Queries
Heavy hitters and frequency measurements are fundamental in many network...
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04/24/2018
Learning Software Constraints via Installation Attempts
Modern software systems are expected to be secure and contain all the la...
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04/04/2018
A Deterministic Distributed 2-Approximation for Weighted Vertex Cover in O( n/ ^2) Rounds
We present a deterministic distributed 2-approximation algorithm for the...
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12/05/2017
