To create today is to create dangerously. Any publication is an act, and that act exposes one to the passions of an age that forgives nothing.
Albert Camus
2021
- (upcoming) EURO 2021, 31st European Conference on Operations Research, Athens, Greece.
- Analysis of Line Search and Trust Region Methods with Noise
- (upcoming, virtual) 3rd IMA and OR Society Conference on Mathematics of Operational Research.
- Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization
- (upcoming, virtual) CSE 2021, SIAM Conference on Computational Science and Engineering.
- A Symmetric Blockwise Truncated Optimization Algorithm for Machine Learning
2020
- (virtual) INFORMS Annual Meeting 2020, Institute for Operations Research and the Management Sciences Conference, National Harbor, MD.
- Analysis Of A Generic Line Search Method With Noise: Algorithms, Convergence Rates And Gradient Approximation. (slides)
- (postponed due to COVID-19) DataX Workshop (September 2020): Old and New Open Questions in Optimization, Princeton University, Princeton, NJ.
- Limited-Memory BFGS with Displacement Aggregation.
- (postponed due to COVID-19) SIOPT 2020, SIAM Conference on Optimization, Hong Kong.
- Global Convergence Rate Analysis of a Line Search Algorithm with Noise.
- (postponed due to COVID-19) MDS 2020: SIAM Conference on Mathematics of Data Science, Cincinnati, OH.
- Sampled Quasi-Newton Methods For Deep Learning.
- JMM 2020, Joint Mathematics Meetings, Denver, CO.
- A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization: Algorithms, Convergence Analysis and Noise. (slides)
2019
- Numerical Analysis and Scientific Computing Seminar, November 2019, Courant Institute of Mathematical Sciences, New York University, New York, NY.
- Limited-Memory BFGS with Displacement Aggregation. (slides)
- INFORMS Annual Meeting 2019, Institute for Operations Research and the Management Sciences Conference, Seattle, WA.
- Quasi-Newton Methods For Deep Learning: Forget The Past, Just Sample. (slides)
- Young Researchers Workshop 2019, ORIE, Cornell University, Ithaca, NY.
- Global Convergence Rate Analysis of a Generic Line Search Algorithm with Noise. (slides)
- ICCOPT 2019, International Conference on Continuous Optimization, Berlin, Germany.
- Aggregated Quasi-Newton Methods. (slides)
- INFORMS PhD Seminar 2019, Lehigh University, Bethlehem, PA.
- A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization. (slides)
- CSE 2019, SIAM Conference on Computational Science and Engineering, Spokane, WA.
- Scaling up and Randomizing Derivative-Free Optimization for Machine Learning. (slides)
2018
- INFORMS Annual Meeting 2018, Institute for Operations Research and the Management Sciences Conference, Phoenix, AZ.
- Stochastic Quasi-Newton Methods – Past, Present and Future. (slides)
- 2nd NSF TRIPODS PI Workshop 2018, University of California, Santa Cruz, CA
- Do we Need 2nd Order Methods in Machine Learning? (poster)
- MOPTA 2018, Modeling and Optimization: Theory and Applications, Bethlehem, PA.
- Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods. (slides)
- ISMP 2018, International Symposium on Mathematical Programming, Bordeaux, France.
- Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods. (slides)
- SPIE-MRSEC Student Seminar Series 2018, Northwestern University, Evanston, IL.
- Methods for Large Scale Nonlinear and Stochastic Optimization. (slides)
2017
- OptML Seminar 2017, Lehigh University, Bethlehem, PA.
- Stochastic Newton and Stochastic Quasi-Newton Methods for Nonlinear Optimization. (slides)
- INFORMS Annual Meeting 2017, Institute for Operations Research and the Management Sciences Conference, Houston, TX.
- Derivative-Free Optimization via Quasi-Newton Methods. (slides)
- IFORS 2017, International Federations on Operations Research Societies Conference, Quebec city, Canada.
- Balancing Computation and Communication in Distributed Optimization. (slides)
- MMLS 2017, Midwest Machine Learning Symposium, Chicago, IL.
- Are Newton-Sketch and Subsampled Newton Methods Effective in Practice? (poster)
- SIOPT 2017, SIAM Conference on Optimization, Vancouver, Canada.
- A Numerical Investigation of Sketching and Subsampling. (slides)
- ACNTW 2017, Northwestern University, Chicago, IL.
- Are Newton-Sketch and Subsampled Newton Methods Effective in Practice? (poster)
- CASSC 2017, SIAM Student Conference (Chicago area), Evanston, IL.
- A Multi-Batch L-BFGS Method for Machine Learning. (slides)
2016
- NIPS 2016, Neural Information Processing Systems Conference, Barcelona, Spain.
- ECML 2016, European Conference on Machine Learning, Riva del Garda, Italy.
- Fields Institute Workshop on Nonlinear Optimization Algorithms and Industrial Applications 2016, Toronto, Canada.
- A Robust Multi-Batch L-BFGS Method for Machine Learning. (poster)
- CASSC 2016, SIAM Student Conference (Chicago area), Chicago, IL.
- An Adaptive Quasi-Newton Algorithm for Training RNNs. (slides)