Carnegie Mellon University
Machine Learning Parallelism Could Be Adaptive, Composable and Automated
Abstract: In recent years, the pace of innovations in the fields of machine learning has accelerated. To cope with the sheer computational complexity of training large ML models on large datasets, researchers in SysML have created algorithms and systems that parallelize ML training and inference over multiple CPUs or GPUs, or even multiple computing nodes [...]
MSR Thesis Talk – Matt Martone
Title: Design and Control of a Large Modular Hexapod Abstract: Legged robotic systems have made great strides in recent years, but unlike wheeled robots, limbed locomotion does not scale well. Long legs demand huge torques, driving up actuator size and onboard battery mass. This relationship results in massive structures that lack the safety, portability, [...]
Improving Robot and Deep Reinforcement Learning via Quality Diversity and Open-Ended Algorithms
Abstract: Quality Diversity (QD) algorithms are those that seek to produce a diverse set of high-performing solutions to problems. I will describe them and a number of their positive attributes. I will then summarize our Nature paper on how they, when combined with Bayesian Optimization, produce a learning algorithm that enables robots, after being damaged, to adapt in 1-2 minutes [...]
Carnegie Mellon University
Online Kinodynamic Planning for Teams of Aerial Robots in 3-D Workspaces
Abstract: An efficient online planning or replanning methodology is a critical requirement for scalable and responsive real world multi-robot deployments. The need to replan typically stems from the invalidation of existing plans due to incomplete knowledge of the environment, or, from scenarios that necessitate changing goal locations in response to evolving application requirements. In this [...]
Go, fastMRI, and Minecraft: Exploring the limits of AI
Abstract: The application of AI across various domains demonstrates both the promise of existing techniques but also their limitations. In this talk, I explore three recent projects and how they shed light on the progress of AI and the challenges to come. These projects include ELF OpenGo a reimplementation of AlphaZero, fastMRI for reducing the time [...]
Robotics Institute Administrative Staff Winter Tree Lunch
Please join us for our annual Robotics Institute Administrative Staff Winter Tree Decorating Lunch. A light lunch will be provided but staff-created treats will always be welcomed.
Carnegie Mellon University
Expressive Real-time Intersection Scheduling: New Methods for Adaptive Traffic Signal Control
Abstract: Traffic congestion is a widespread problem throughout global metropolitan areas. In this thesis, we consider methods to optimize the performance of traffic signals to reduce congestion. We begin by presenting Expressive Real-time Intersection Scheduling (ERIS), a schedule-driven intersection control strategy that runs independently on each intersection in a traffic network. For each intersection, ERIS [...]
Carnegie Mellon University
Open-world 3D Object Detection
Abstract: Perception for autonomous robots presents a set of unique challenges: finding the right representation for 3D signals, adapting to an open-world setting, and exploiting geometric priors. Successfully detecting objects regardless of their labels lays a solid foundation for safe navigation. I will present two of my recent works in this line. First, I will [...]
Towards Weakly-Supervised Visual Understanding
Abstract: Learning with weak and self-supervisions recently emerged as compelling tools towards leveraging vast amounts of unlabeled or partially-labeled data. In this talk, I will present some of the latest advances in weakly-supervised visual scene understanding from NVIDIA. Specifically, I will summarize and discuss some challenges and potential solutions in weakly-supervised learning, and introduce our [...]