no code implementations • 16 Mar 2024 • Minkyu Choi, Harsh Goel, Mohammad Omama, Yunhao Yang, Sahil Shah, Sandeep Chinchali
The unprecedented surge in video data production in recent years necessitates efficient tools to extract meaningful frames from videos for downstream tasks.
no code implementations • 5 Mar 2024 • Sai Shankar Narasimhan, Shubhankar Agarwal, Oguzhan Akcin, Sujay Sanghavi, Sandeep Chinchali
Current approaches to time series generation often ignore this paired metadata, and its heterogeneity poses several practical challenges in adapting existing conditional generation approaches from the image, audio, and video domains to the time series domain.
no code implementations • 13 Feb 2024 • Po-han Li, Oyku Selin Toprak, Aditya Narayanan, Ufuk Topcu, Sandeep Chinchali
We thus formulate a user-centric online model selection problem and propose a novel solution that combines an open-source encoder to output context and an online learning algorithm that processes this context.
no code implementations • 18 Sep 2023 • Yunhao Yang, Jean-Raphaël Gaglione, Sandeep Chinchali, Ufuk Topcu
The increasing abundance of video data enables users to search for events of interest, e. g., emergency incidents.
no code implementations • 7 Mar 2023 • Oguzhan Akcin, Po-han Li, Shubhankar Agarwal, Sandeep Chinchali
Instead, we propose a cooperative data sampling strategy where geo-distributed AVs collaborate to collect a diverse ML training dataset in the cloud.
no code implementations • 23 Jan 2023 • Manan Gupta, Sandeep Chinchali, Paul Varkey, Jeffrey G. Andrews
Cellular networks are becoming increasingly heterogeneous with higher base station (BS) densities and ever more frequency bands, making BS selection and band assignment key decisions in terms of rate and coverage.
no code implementations • 23 Oct 2022 • Oguzhan Akcin, Robert P. Streit, Benjamin Oommen, Sriram Vishwanath, Sandeep Chinchali
As such, the associated token rewards should gracefully scale with the size of the decentralized system, but should be carefully balanced with consumer demand to manage inflation and be designed to ultimately reach an equilibrium.
no code implementations • 19 Sep 2022 • Yue Yu, Ruihan Zhao, Sandeep Chinchali, Ufuk Topcu
Data-driven predictive control (DPC) is a feedback control method for systems with unknown dynamics.
no code implementations • 20 Apr 2022 • Christos Verginis, Cevahir Koprulu, Sandeep Chinchali, Ufuk Topcu
We develop a reinforcement-learning algorithm that infers a reward machine that encodes the underlying task while learning how to execute it, despite the uncertainties of the propositions' truth values.
no code implementations • 28 Jan 2022 • Jiangnan Cheng, Sandeep Chinchali, Ao Tang
Classical network coding is largely task-agnostic -- the coding schemes mainly aim to faithfully reconstruct data at the receivers, regardless of what ultimate task the received data is used for.
no code implementations • 26 Jan 2022 • Chenyu You, Ruihan Zhao, Fenglin Liu, Siyuan Dong, Sandeep Chinchali, Ufuk Topcu, Lawrence Staib, James S. Duncan
In this work, we present CASTformer, a novel type of adversarial transformers, for 2D medical image segmentation.
no code implementations • 2 Dec 2021 • Manabu Nakanoya, Junha Im, Hang Qiu, Sachin Katti, Marco Pavone, Sandeep Chinchali
Autonomous vehicles (AVs) must interact with a diverse set of human drivers in heterogeneous geographic areas.
no code implementations • 8 Nov 2021 • Hang Qiu, Ioanna Vavelidou, Jian Li, Evgenya Pergament, Pete Warden, Sandeep Chinchali, Zain Asgar, Sachin Katti
The key challenge is that there is not much visibility into ML inference execution on edge devices, and very little awareness of potential issues during the edge deployment process.
1 code implementation • 5 Oct 2021 • Jiangnan Cheng, Ao Tang, Sandeep Chinchali
Local differential privacy (LDP) can be adopted to anonymize richer user data attributes that will be input to sophisticated machine learning (ML) tasks.
1 code implementation • NeurIPS 2021 • Jiangnan Cheng, Marco Pavone, Sachin Katti, Sandeep Chinchali, Ao Tang
Sharing forecasts of network timeseries data, such as cellular or electricity load patterns, can improve independent control applications ranging from traffic scheduling to power generation.
no code implementations • 12 Dec 2020 • Sandeep Chinchali, Evgenya Pergament, Manabu Nakanoya, Eyal Cidon, Edward Zhang, Dinesh Bharadia, Marco Pavone, Sachin Katti
Today's robotic fleets are increasingly measuring high-volume video and LIDAR sensory streams, which can be mined for valuable training data, such as rare scenes of road construction sites, to steadily improve robotic perception models.
1 code implementation • 17 Nov 2020 • Joseph Lubars, Harsh Gupta, Sandeep Chinchali, Liyun Li, Adnan Raja, R. Srikant, Xinzhou Wu
We consider the problem of designing an algorithm to allow a car to autonomously merge on to a highway from an on-ramp.
no code implementations • 6 Nov 2020 • Manabu Nakanoya, Sandeep Chinchali, Alexandros Anemogiannis, Akul Datta, Sachin Katti, Marco Pavone
However, today's representations for sensory data are mostly designed for human, not robotic, perception and thus often waste precious compute or wireless network resources to transmit unimportant parts of a scene that are unnecessary for a high-level robotic task.
1 code implementation • ICLR 2020 • Tianshu Chu, Sandeep Chinchali, Sachin Katti
This paper considers multi-agent reinforcement learning (MARL) in networked system control.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 15 Feb 2019 • Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone
In this paper, we formulate a novel Robot Offloading Problem --- how and when should robots offload sensing tasks, especially if they are uncertain, to improve accuracy while minimizing the cost of cloud communication?