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Portfolio item number 2
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publications
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2).
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Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3).
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Paper Shit Number 4
Published in GitHub Journal of Bugs, 2024
This paper is about fixing template issue #693.
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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Best-of-K Bandits
Published in COLT, 1900
Gradient Descent Converges to Minimizers
Published in COLT, 1900
Low-rank Solutions of Linear Matrix Equations via Procrustes Flow
Published in ICML, 1900
The Simulator: Towards a Richer Understanding of Adaptive Sampling in the Moderate-Confidence Regime
Published in COLT, 1900
Delayed Impact of Fair Machine Learning
Published in ICML, 1900
Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification
Published in COLT, 1900
Tight Query Complexity Lower Bounds for PCA via Finite Sample Deformed Wigner Law
Published in STOC, 1900
Approximate Ranking from Pairwise Comparisons
Published in AISTATS, 1900
Balancing Competing Objectives for Welfare-Aware Machine Learning with Imperfect Data
Published in The Neural Information Processing Systems Joint Workshop on AI for Social Good, 1900
First-order Methods Almost Always Avoid Saddle Points
Published in Mathematical Programming (pg. 1-27), 1900
Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs”
Published in NeurIPS, 1900
The Implicit Fairness Criterion of Unconstrained Learning
Published in ICML, 1900
Learning Linear Dynamical Systems with Semi-Parametric Least Squares
Published in COLT, 1900
First-order Methods Almost Always Avoid Saddle Points
Published in Mathematical Programming (pg. 1-27), 1900
A Successive-Elimination Approach to Adaptive Robotic Source Seeking
Published in Transactions on Robotics, 1900
The gradient complexity of linear regression
Published in COLT, 1900
Improper Learning for Nonstochastic Control
Published in COLT, 1900
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
Published in ICML, 1900
Logarithmic Regret for Online Control with Adversarial Disturbances
Published in ICML, 1900
Naive Exploration is Optimal for Online LQR
Published in ICML, 1900
Reward-Free Exploration for Reinforcement Learning
Published in ICML, 1900
Constrained episodic reinforcement learning in concave-convex and knapsack settings
Published in NeurIPS, 1900
Making Non-Stochastic Control (Almost) as Easy as Stochastic
Published in NeurIPS, 1900
Learning a Linear Quadratic Regular from Nonlinear Observations
Published in NeurIPS, 1900
Towards a Dimension-Free Understanding of Adaptive Linear Control
Published in COLT, 1900
Corruption Robust Exploration in Episodic Reinforcement Learning
Published in COLT, 1900
Task-Optimal Exploration in Linear Dynamical Systems
Published in COLT, 1900
On Stability of Nonlinear Receding Horizon Control: A Geometric Perspective
Published in CDC, 1900
Bayesian decision-making under misspecified priors with applications to meta-learning
Published in NeurIPS, 1900
Stabilizing Dynamical Systems via Policy Gradient Methods
Published in NeurIPS, 1900
Online Control of Unknown Time-Varying Dynamical Systems
Published in NeurIPS, 1900
Beyond No Regret: Instance-Dependent PAC Reinforcement Learning
Published in COLT, 1900
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
Published in ICML, 1900
Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes
Published in ICML, 1900
Do Differentiable Simulators Give Better Policy Gradients?
Published in ICML, 1900
Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions
Published in NeurIPS, 1900
Globally Convergent Policy Search over Dynamic Filters for Output Estimation
Published in NeurIPS, 1900
Learning to Extrapolate: A Transductive Approach
Published in NeurIPS 2022 Workshop on Distribution Shifts (DistShift), 1900
Pathologies and Challenges of Using Differentiable Simulators in Policy Optimization for Contact-Rich Manipulation
Published in ICRA 2022 Workshop: Reinforcement Learning for Contact-Rich Manipulation, 1900
Learning to Extrapolate: A Transductive Approach
Published in ICLR, 1900
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective
Published in COLT, 1900
Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making
Published in COLT, 1900
Statistical Learning under Heterogenous Distribution Shift
Published in ICML, 1900
Imitating Complex Trajectories: Bridging Low-Level Stability and High-Level Behavior
Published in Frontiers4LCD Workshop, ICML, 1900
The Power of Learned Locally Linear Models for Nonlinear Policy Optimization
Published in ICML, 1900
Non-Euclidean Motion Planning with Graphs of Geodesically-Convex Sets
Published in RSS, 1900
Exploration and Incentives in Reinforcement Learning
Published in Operations Research, 1900
Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior
Published in NeurIPS, 1900
Smoothed Online Learning for Prediction in Piecewise Affine Systems
Published in NeurIPS, 1900
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability
Published in NeurIPS, 1900
Paper Title Number 4
Published in GitHub Journal of Bugs, 2024
This paper is about fixing template issue #693.
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression
Published in ICLR, 1900
Fleet Policy Learning via Weight Merging and An Application to Robotic Tool-Use
Published in ICLR, 1900
Constrained Bimanual Planning with Analytic Inverse Kinematics
Published in ICRA, 1900
Faster Algorithms for Growing Collision-Free Convex Polytopes in Robot Configuration Space
Published in ISRR, 1900
Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion
Published in Neurips, 1900
PhD Thesis: Statistical Complexity and Regret in Linear Control
Published in UC Berkeley Department of Electrical Engineering and Computer Science, 1900
On the Gap Between Strict-Saddles and True Convexity: An Omega(log d) Lower Bound for Eigenvector Approximation
Published in Arxiv, 1900
Adaptive Sampling for Convex Regression
Published in Formerly R&R at Annals of Statistics, 1900
On the Randomized Complexity of Minimizing a Convex Quadratic Function
Published in Arxiv, 1900
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).
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Diffusion Policy Policy Optimization
Published in ArXiv Preprint, 1900
Standard_pub_template
Published in , 1900
title: “Paper Title Number 1 MEh” collection: standard_pubs category: manuscripts authors: award: ?? year: 2024 venue: ‘Journal 1’ slidesurl: ‘http://academicpages.github.io/files/slides1.pdf’ paperurl: ‘http://academicpages.github.io/files/paper1.pdf’
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.
Introduction to Machine Learning
old, UC Berkeley, 1900
Convex Optimization and Approximation
old, UC Berkeley, 1900