Search Results for author: Mohammad Alizadeh

Found 24 papers, 10 papers with code

Updating Street Maps using Changes Detected in Satellite Imagery

no code implementations13 Oct 2021 Favyen Bastani, Songtao He, Satvat Jagwani, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden, Mohammad Amin Sadeghi

To address this challenge, much work has studied automatically processing geospatial data sources such as GPS trajectories and satellite images to reduce the cost of maintaining digital maps.

Efficient Video Compression via Content-Adaptive Super-Resolution

1 code implementation ICCV 2021 Mehrdad Khani, Vibhaalakshmi Sivaraman, Mohammad Alizadeh

SRVC decodes the video by passing the decompressed low-resolution video frames through the (time-varying) super-resolution model to reconstruct high-resolution video frames.

Super-Resolution Video Compression

Cortex: Harnessing Correlations to Boost Query Performance

no code implementations12 Dec 2020 Vikram Nathan, Jialin Ding, Tim Kraska, Mohammad Alizadeh

Unlike prior work, Cortex can adapt itself to any existing primary index, whether single or multi-dimensional, to harness a broad variety of correlations, such as those that exist between more than two attributes or have a large number of outliers.

Neural Large Neighborhood Search

no code implementations NeurIPS Workshop LMCA 2020 Ravichandra Addanki, Vinod Nair, Mohammad Alizadeh

Results on several datasets show that it is possible to learn a neighbor selection policy that allows LNS to efficiently find good solutions.

Combinatorial Optimization

Real-world Video Adaptation with Reinforcement Learning

no code implementations28 Aug 2020 Hongzi Mao, Shannon Chen, Drew Dimmery, Shaun Singh, Drew Blaisdell, Yuandong Tian, Mohammad Alizadeh, Eytan Bakshy

Client-side video players employ adaptive bitrate (ABR) algorithms to optimize user quality of experience (QoE).

Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads

no code implementations23 Jun 2020 Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska

Filtering data based on predicates is one of the most fundamental operations for any modern data warehouse.

Real-Time Video Inference on Edge Devices via Adaptive Model Streaming

1 code implementation ICCV 2021 Mehrdad Khani, Pouya Hamadanian, Arash Nasr-Esfahany, Mohammad Alizadeh

Real-time video inference on edge devices like mobile phones and drones is challenging due to the high computation cost of Deep Neural Networks.

Knowledge Distillation Semantic Segmentation +2

RoadTagger: Robust Road Attribute Inference with Graph Neural Networks

1 code implementation28 Dec 2019 Songtao He, Favyen Bastani, Satvat Jagwani, Edward Park, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Samuel Madden, Mohammad Amin Sadeghi

The usage of graph neural networks allows information propagation on the road network graph and eliminates the receptive field limitation of image classifiers.

Learning Multi-dimensional Indexes

no code implementations3 Dec 2019 Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska

Scanning and filtering over multi-dimensional tables are key operations in modern analytical database engines.

Learning Generalizable Device Placement Algorithms for Distributed Machine Learning

1 code implementation NeurIPS 2019 Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta, Hongzi Mao, Mohammad Alizadeh

We present Placeto, a reinforcement learning (RL) approach to efficiently find device placements for distributed neural network training.

Inferring and Improving Street Maps with Data-Driven Automation

no code implementations2 Oct 2019 Favyen Bastani, Songtao He, Satvat Jagwani, Edward Park, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden, Mohammad Amin Sadeghi

Through an evaluation on a large-scale dataset including satellite imagery, GPS trajectories, and ground-truth map data in forty cities, we show that Mapster makes automation practical for map editing, and enables the curation of map datasets that are more complete and up-to-date at less cost.

Prism: Scaling Bitcoin by 10,000x

2 code implementations25 Sep 2019 Lei Yang, Vivek Bagaria, Gerui Wang, Mohammad Alizadeh, David Tse, Giulia Fanti, Pramod Viswanath

Bitcoin is the first fully decentralized permissionless blockchain protocol and achieves a high level of security: the ledger it maintains has guaranteed liveness and consistency properties as long as the adversary has less compute power than the honest nodes.

Distributed, Parallel, and Cluster Computing Cryptography and Security Networking and Internet Architecture

Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning

2 code implementations20 Jun 2019 Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta, Hongzi Mao, Mohammad Alizadeh

Unlike prior approaches that only find a device placement for a specific computation graph, Placeto can learn generalizable device placement policies that can be applied to any graph.

Machine-Assisted Map Editing

no code implementations17 Jun 2019 Favyen Bastani, Songtao He, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden

Systems to automatically infer road network graphs from aerial imagery and GPS trajectories have been proposed to improve coverage of road maps.

graph construction

Adaptive Neural Signal Detection for Massive MIMO

1 code implementation11 Jun 2019 Mehrdad Khani, Mohammad Alizadeh, Jakob Hoydis, Phil Fleming

We propose MMNet, a deep learning MIMO detection scheme that significantly outperforms existing approaches on realistic channels with the same or lower computational complexity.

Understanding & Generalizing AlphaGo Zero

no code implementations ICLR 2019 Ravichandra Addanki, Mohammad Alizadeh, Shaileshh Bojja Venkatakrishnan, Devavrat Shah, Qiaomin Xie, Zhi Xu

AlphaGo Zero (AGZ) introduced a new {\em tabula rasa} reinforcement learning algorithm that has achieved superhuman performance in the games of Go, Chess, and Shogi with no prior knowledge other than the rules of the game.

Decision Making

Learning Scheduling Algorithms for Data Processing Clusters

no code implementations3 Oct 2018 Hongzi Mao, Malte Schwarzkopf, Shaileshh Bojja Venkatakrishnan, Zili Meng, Mohammad Alizadeh

Efficiently scheduling data processing jobs on distributed compute clusters requires complex algorithms.

Restructuring Endpoint Congestion Control

1 code implementation SIGCOMM '18 2018 Akshay Narayan, Frank Cangialosi, Deepti Raghavan, Prateesh Goyal Srinivas Narayana, Radhika Mittal, Mohammad Alizadeh, Hari Balakrishnan

Each datapath—such as the Linux kernel TCP, UDP-based QUIC, or kernel-bypass transports like mTCP-on-DPDK—summarizes information about packet round-trip times, receptions, losses, and ECN via a well-defined interface to algorithms running in the off-datapath Congestion Control Plane (CCP).

Variance Reduction for Reinforcement Learning in Input-Driven Environments

no code implementations ICLR 2019 Hongzi Mao, Shaileshh Bojja Venkatakrishnan, Malte Schwarzkopf, Mohammad Alizadeh

We consider reinforcement learning in input-driven environments, where an exogenous, stochastic input process affects the dynamics of the system.

Meta-Learning Object Tracking +1

Graph2Seq: Scalable Learning Dynamics for Graphs

no code implementations ICLR 2018 Shaileshh Bojja Venkatakrishnan, Mohammad Alizadeh, Pramod Viswanath

By not limiting the representation to a fixed dimension, Graph2Seq scales naturally to graphs of arbitrary sizes and shapes.

Combinatorial Optimization Time Series

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