My main area of research lies at the intersection of quantum computing and learning theory, and involves developing algorithms for discriminative and generative tasks under various noise models and proving theoretical bounds for convergence, generalization, and speedups.
Office: B-513, New Academic block, IIITD
Email: sagnikc [at] iiitd [dot] ac [dot] in
Efficient Quantum Agnostic Improper Learning of Decision Trees.
Abstract: This work answers two open questions. We give the first efficient quantum boosting algorithms in the agnostic setting by providing a quantum version of the Kalai-Kanade potential boosting algorithm. This algorithm shows the standard quadratic speedup in the VC dimension of the weak learner compared to the classical case. Using our boosting algorithm as a subroutine, we give the first quantum algorithm for agnostically learning decision trees in polynomial running time without using membership queries. To the best of our knowledge, this is the first algorithm (quantum or classical) to do so. Learning decision trees without membership queries is hard (and an open problem) in the standard classical realizable setting. In general, even coming up with weak learners in the agnostic setting is a challenging task. We show how to construct a quantum agnostic weak learner using standard quantum algorithms, which is of independent interest for designing ensemble learning setups.
Quantum boosting using domain-partitioning hypotheses.
Accepted at QTML'22 for a short talk. Poster accepted at QIP'22.
Abstract: This work answers an open question regarding the existence of quantum boosting algorithms for weak learners with non-binary hypotheses. Our QRealBoost algorithm has provable theoretical guarantees for convergence, generalization bounds, and quantum speedup (using noisy and probabilistic quantum subroutines) versus both classical boosting algorithms and other quantum adaptive boosting algorithms. We also perform empirical evaluations and report encouraging observations on quantum simulators by benchmarking the convergence performance of QRealBoost against QAdaBoost, AdaBoost, and RealBoost on a subset of the MNIST dataset and Breast Cancer Wisconsin dataset.
Applying QAOA+ to the graph matching problem.
Extended Abstract accepted at AQIS'20. Poster accepted at QIP'21.
Abstract: Counting problems with respect to matchings are #P-hard; which precludes the existence of efficient deterministic classical algorithms for creating superpositions over all distinct matchings and all maximal matchings. In this work, we try to achieve these superpositions for 2-regular graphs by designing polynomial depth QAOA+ style circuits with novel mixing operators. We also evaluate the advantages of starting with the W-state and empirically demonstrate that for 2-regular graphs, our algorithm has a better lower bound for the expected matching size compared to the uniform distribution over all matchings.
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Refresher Module, 2021
This was a short course I taught at IIIT-Delhi as part of a refresher module on
Operating Systems during the Monsoon 2022 semester. The focus of the course was
revising the behaviour of the C-compiler with respect to the system memory at an
introductory level. The main topics covered were control flow, pointers, arrays,
strings, dynamic memory allocation, intermediate stages of compilation, and using
tools like gdb and valgring for debugging.
Lecture 1, Lecture 2, Lecture 3.
Faculty Development Program, 2020
This was an invited talk at the Faculty Development Program at the JNTU, Anantapuram, India. The talk focuses on giving an overview of Quantum Optimization and Quantum Machine Learning. My Slides.
Evariste Invited Talk, 2020
This was a talk I gave for Evariste – IIITD’s Theory and Math club.
Abstract: Shallow Quantum Circuits are the quantum analogs of constant depth classical circuits, which became a focal point of interest following the proof of unconditional separation between SQC’s and constant depth bounded fan-in classical circuits by Bravyi et al.
We discussed the motivations behind research on SQC’s and some interesting separation results (noisy as well as noiseless) between SQC’s and strictly local classical circuits, geometrically local classical circuits, and constant depth classical circuits. Slides and Video (Video is internal to IIITD).
Complexity Theory Presentations, 2020
This was a presentation at my Complexity Theory Course in the Fall of 2020. The talk
focuses on the paper demonstrating Oracle Separation of BQP and PH by
Raz and Avishay Tal, and explains the main concepts and proof techniques explored in
the paper. The total
duration of the talk was 50 minutes with 10 minutes for Q&A.
Original Paper Oracle separation of BQP and PH (Raz-Tal).
Gong Show Talk, 2019
This was a Gong Show talk I gave at the 4th Advanced School of CSE, hosted by the Israel Institute of Advanced Studies, Jerusalem. I have linked the slides, and the video below. I have also provided my revised notes which I had contributed towards the “Teach Me Quantum” category of the IBMQ awards (2019-2020), in which we won the second place prize. My Notes, Slides.
Young Quantum - 2023
I was selected to attend YouQu-2023, which is a meeting for PhD scholars and post-doctoral fellows to be organized by the Quantum Information and Computation group of Harish-Chandra Research Institute (HRI), Prayagraj (Allahabad), which aims to provide a platform for young researchers working in the broad areas of quantum information theory and related fields to encourage discussions and stimulate new collaborations and interactions.
QISE 2021 Workshop
I was the only grad student to be a part of the 2021 workshop on Quantum Information Science and Engineering (colocated with FSTTCS 2021) organizing committee. This is the website for the workshop (desktop browsers recommended).
2020 Workshop on Boolean Functions
I was selected to attend a workshop on Sensitivity, Query Complexity, Communication Complexity and Fourier Analysis of Boolean Functions organized by the Indian Statistical Institute, Calcutta.
The 4th Advanced Winter School by IIAS 2019
I was one of the two grad students from India to be selected for this prestigious winter school organized by the Israel Institute for Advanced studies, at the Hebrew University of Jerusalem. The school served as brief introductions to the fields of quantum algorithms, quantum error correction, quantum supremacy, delegation and verification, interactive proofs, cryptography, and Hamiltonian complexity along with detailed TA sessions for a week. Check out the youtube video of my Gong Talk on the HHL algorithm (starts around the 6 min mark).
IBMQ Awards 2019
We finished runners up in the “Teach Me Quantum” category of the IBMQ awards (2019-2020). Check out the Github repo for the course here. We designed an 11-week undergraduate course covering concepts in quantum physics, quantum chemistry, mathematics, complexity theory, cryptography, and ensemble based learning and much more. The main goal of this course is to serve as a starting point for people from backgrounds in physics, mathematics, chemistry and computer science with exercises tailored specifically towards these domains.
Free Courses and Books (TCS)
- Randomized Algorithms by James Aspnes
- Advanced Complexity Theory by Hamed Hatami
- Computational Complexity by Manoj M. Prabhakaran
- Communication Complexity by Mark Bun
- Computational Social Choice by Rohit Vaish
- Analytical Toolkit in Computer Science by Hemanta K. Maji
- A Theorist's toolkit by Ryan O'Donnell
- Data Stream Algorithms by Amit Chakraborti
- Theory of Metric Embeddings by Harald Räcke
- Lecture notes on metric embeddings by Jiří Matoušek
- Algorithms book by Jeff Erickson
- Introduction to Theoretical Computer Science by Boaz Barak
- Lecture Notes by Tim Roughgarden
- Analysis of Boolean Functions by Ryan O'Donnell
- Probabilistic Method in Combinatorics by Yufei Zhao
Free Courses and Books (Quantum)
- Introduction to Quantum Computing by Sevag Gharibian
- Introduction to Quantum Information Theory by Mark M. Wilde
- Quantum Complexity Theory by Scott Aaronson
- Quantum Complexity Theory by Sevag Gharibian
- Quantum Computing lecture notes by Ronald de Wolf
Free Courses and Books (Learning Theory)
- Sample Complexity and Uniform Convergence Part 1 and Part 2: Eli Upfal
- Machine Learning by Ronald Rivest and Mona Singh
- Machine Learning Theory by Akshay Krishnamurthy
- Foundations of Modern Machine Learning by Nika Haghtalab
- Learning Theory by Ambuj Tewari
- Machine Learning Theory by Maria Florina Balcan
- Understanding ML by Shai Shalev-Shwartz and Shai Ben-David
- Convex Optimization: Algorithms and Complexity by Sébastien Bubeck
- 2019 Mathematics of Machine Learning Graduate Summer School
- Topics and Techniques in Distribution Testing by Clément Canonne
Expository Resources (TCS)
- Metric Embeddings (FOCS22 workshop) by Hung Le
- Five Proofs of Chernoff's Bound with Applications by Wolfgang Mulzer
- Edmond's Blossom Algorithm by James S. Plank
- Tossing a biased coin by Michael Mitzenmacher
- Determining the direction of a coin's bias by William Hoza
- Part 1 and Part 2 on Multivariate Gaussians by Chuong B. Do
- Understanding Ladner's Theorem by Sanjoy Das
- Reservoir Sampling: Florian Hartmann, Stephen N. Pallone
- Morris' algorithm by Gregory Gundersen
- The Unique Games Conjecture by Scott Aaronson
- Hastad's switching lemma by Victor Lecomte
- Plancherel's trick by Victor Lecomte
Expository Resources (Quantum)
- Youtube playlist on Density Matrix and Mixed States by Diego Emilio
- QAOA literature survey by Kunal Marwaha
- A list of Open and Solved quantum problems by IQOQI Vienna
Expository Resources (Learning Theory)
- Website on Algorithms With Predictions
- Diffusion Models : Calvin Luo, Lilian Weng, CVPR 2022 Tutorial
- Generative Flows : Lilian Weng, Yoshua Bengio
- Learning Theory Notes by Gene Li
- Dijkstra's in Disguise by Eric Jang
Expository Resources (others)
- The Value of Science by Richard Feynman
- The Limits of Quantum Computers by Scott Aaronson
- Advice to PhD students by Oded Goldreich
- 3 qualities of successful PhD students by Matt Might
- Writing a good introduction by Jim Kurose
- How to write a ML paper by Jakob Foerster
- Writing Technical Articles by Henning Schulzrinne
- The importance of stupidity in scientific research by Martin A. Schwartz
- Presenting a Technical Talk by Nick Feamster
- Top 10 ways to Lose your Audience