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ESE Spring Seminar – “Wavelength-Encoded Nanolaser Particles for Highly Multiplexed Single-Cell Analysis”

Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

Understanding single-cell heterogeneity in biological systems is considered the holy grail of biomedicine. However, conventional single-cell analysis methods are constrained by the destructive readout process of DNA barcodes and the broad emission linewidths of fluorescence barcodes, limiting their ability to capture dynamic information and achieve high multiplexing capabilities. This seminar explores the transformative potential of […]

IDEAS/STAT Optimization Seminar: “The Size of Teachers as a Measure of Data Complexity: PAC-Bayes Excess Risk Bounds and Scaling Laws”

Amy Gutmann Hall, Room 414 3333 Chestnut Street, Philadelphia, United States

Zoom link: https://upenn.zoom.us/j/98220304722 Abstract: We study the generalization properties of neural networks through the lens of data complexity.  Recent work by Buzaglo et al. (2024) shows that random (nearly) interpolating networks generalize, provided there is a small ``teacher'' network that achieves small excess risk. We give a short single-sample PAC-Bayes proof of this result and […]

IDEAS/STAT Optimization Seminar: “Stochastic-Gradient-based Algorithms for Solving Nonconvex Constrained Optimization Problems”

Amy Gutmann Hall, Room 615

Zoom link: https://upenn.zoom.us/j/98220304722   Abstract I will present recent work by my research group on the design and analysis of stochastic-gradient-based algorithms for solving nonconvex constrained optimization problems, which may arise, for example, in informed supervised learning.  I will focus in particular on algorithmic strategies that have consistently been shown to exhibit the best practical […]

IDEAS/STAT Optimization Seminar: “Gradient Equilibrium in Online Learning”

Amy Gutmann Hall, Room 414 3333 Chestnut Street, Philadelphia, United States

We present a new perspective on online learning that we refer to as gradient equilibrium: a sequence of iterates achieves gradient equilibrium if the average of gradients of losses along the sequence converges to zero. In general, this condition is not implied by, nor implies, sublinear regret. It turns out that gradient equilibrium is achievable […]

PICS Colloquium: Multiscale simulations of soft matter: from block copolymers to biomolecular condensates

PICS Conference Room 534 - A Wing , 5th Floor 3401 Walnut Street, Philadelphia, PA, United States

Polymers are ubiquitous in both synthetic and biological materials and underlie technologies as diverse as surfactants, adhesives, proteins and DNA. One of the defining features of all polymeric materials is that they are characterized by a wide range of length scales, often involving phenomena that span nanometers to microns. This hierarchy of length scales presents […]

IDEAS/STAT Optimization Seminar: Resilient Distributed Optimization for Cyberphysical Systems

Amy Gutmann Hall, Room 414 3333 Chestnut Street, Philadelphia, United States

Zoom link: https://upenn.zoom.us/j/98220304722   Abstract: This talk considers the problem of resilient distributed multi-agent optimization for cyberphysical systems in the presence of malicious or non-cooperative agents. It is assumed that stochastic values of trust between agents are available which allows agents to learn their trustworthy neighbors simultaneously with performing updates to minimize their own local […]

ESE 5160 Special Lecture: “Taking RoboRacer Off-Road: Learning Extreme Off-Road Mobility”

Towne 327

In this guest lecture, we will cover two recent research thrusts from the RobotiXX lab in taking RoboRacer off-road: high-speed off-road navigation and wheeled mobility on vertically challenging terrain. For high-speed off-road navigation, we will introduce a sequential line of work with every work inspired by and built upon its prior work, ranging from inverse […]

ESE Guest Seminar – “Efficient Computing for AI and Robotics: From Hardware Accelerators to Algorithm Design”

Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

The compute demands of AI and robotics continue to rise due to the rapidly growing volume of data to be processed; the increasingly complex algorithms for higher quality of results; and the demands for energy efficiency and real-time performance. In this talk, we will discuss the design of efficient tailored hardware accelerators and the co-design […]

IDEAS/STAT Optimization Seminar: “Negative Stepsizes Make Gradient-Descent-Ascent Converge”

Amy Gutmann Hall, Room 414 3333 Chestnut Street, Philadelphia, United States

Zoom link: https://upenn.zoom.us/j/98220304722 Abstract: Solving min-max problems is a central question in optimization, games, learning, and controls. Arguably the most natural algorithm is Gradient-Descent-Ascent (GDA), however since the 1970s, conventional wisdom has argued that it fails to converge even on simple problems. This failure spurred the extensive literature on modifying GDA with extragradients, optimism, momentum, anchoring, […]

PICS Colloquium: Learning to Model the World (and Yourself) from Vision

PICS Conference Room 534 - A Wing , 5th Floor 3401 Walnut Street, Philadelphia, PA, United States

In this talk, I will discuss recent publications from my group that attempt at learning models of the world and the effect of the actions of an agent within that world self-supervised, solely via interaction. In particular, I will discuss the potential and challenges of video generative models as a candidate for such a world […]