Nov 16 2022

Extremal Pattern-Avoiding Words

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Wednesday, November 16, 2022
12:15 PM - 1:15 PM
Type: Seminars | Graduate Combinatorics Seminar
Presenter(s): Natasha Ter-Saakov - Rutgers University
Consider a word (a sequence of letters) on an alphabet of size k. This word contains a pattern if it contains (consecutive) subwords that realize the pattern and avoids it
Nov 14 2022

Logarithmically Larger Deletion Codes

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Monday, November 14, 2022
2:00 PM - 3:00 PM
Type: Seminars | Rutgers Discrete Mathematics Seminar
Presenter(s): Noah Kravitz - Princeton University
The deletion distance between two binary words of length n is the smallest k such that the words have a common subsequence of length n-k. A set of binary words
Nov 10 2022

The Arithmetic-Periodicity of the game CUT

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Thursday, November 10, 2022
5:00 PM - 6:00 PM
Type: Seminars | Experimental Math Seminar
Presenter(s): Paul Ellis - Rutgers University
CUT is a class of partition games played on a finite number of finite piles of tokens. We will discuss some interesting properties of these games. Link to video: https://vimeo.com/772201058
Nov 09 2022

Simple Combinatorial Construction of the $k^{o(1)}$-Lower Bound for Approximating the Parameterized $k$-Clique

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Wednesday, November 9, 2022
11:00 AM - 12:15 PM
Type: Seminars | Theoretical Computer Science Seminar
Presenter(s): Bundit Laekhanukit - Shanghai University of Finance and Economics
In a recent breakthrough [STOC'21], Lin proves that there is no fpt-algorithm that can approximate the clique problem with any constant ratio unless FPT= W[1]. This is subsequently improved by
Nov 09 2022

Some Random Algebra and Rational Exponents

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Wednesday, November 9, 2022
12:15 PM - 1:15 PM
Type: Seminars | Graduate Combinatorics Seminar
Presenter(s): Sam Spiro - Rutgers University
Let ex(n,F) denote the maximum number of edges that an F-free graph can have. One of the few ways we know how to get general lower bounds on ex(n,F) is
Nov 09 2022

Robust Mendelian Randomization in the Presence of Many Weak Instruments and Widespread Horizontal Pleiotropy

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Wednesday, November 9, 2022
11:50 AM - 12:50 PM
Type: Seminars | DATA-INSPIRE TRIPODS Seminars
Presenter(s): Ting Ye - University of Washington
Mendelian randomization (MR) has become a popular approach to studying the effect of a modifiable exposure on an outcome by using genetic variants as instrumental variables (IVs). Two distinct challenges
Nov 02 2022

Reproducibility in Learning

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Wednesday, November 2, 2022
11:00 AM - 12:15 PM
Type: Seminars | Theoretical Computer Science Seminar
Presenter(s): Jessica Sorrell - University of Pennsylvania
Reproducibility is vital to ensuring scientific conclusions are reliable, but failures of reproducibility have been a major issue in nearly all scientific areas of study in recent decades. A key
Nov 02 2022

Planar Turàn Number: Plane Graph Decomposition and Contribution Method

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Wednesday, November 2, 2022
12:15 PM - 1:15 PM
Type: Seminars | Graduate Combinatorics Seminar
Presenter(s): Zeyu Zheng - Rutgers University
One of the most famous results in extremal graph theory is Turàn's theorem, which leads to a series of remarkable results which we now consider Turàn-type problems. The study of
Nov 02 2022

Sufficient Reductions in Regression with Mixed Predictors

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Wednesday, November 2, 2022
11:50 AM - 12:50 PM
Type: Seminars | DATA-INSPIRE TRIPODS Seminars
Presenter(s): Efstathia Bura - Vienna University of Technology
Most data sets comprise of measurements on continuous and categorical variables. Yet, modeling high- dimensional mixed predictors has received limited attention in the regression and classification statistical literature. We study
Oct 31 2022

Product Free Sets in the Alternating Group

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Monday, October 31, 2022
2:00 PM - 3:00 PM
Type: Seminars | Rutgers Discrete Mathematics Seminar
Presenter(s): Noam Lifshitz - Institute for Advanced Study
A subset of a group is said to be product free if it does not contain the product of two elements in it. We consider how large can a product
Oct 28 2022

IBM/DIMACS/DATA-INSPIRE Workshop on Bridging Game Theory and Machine Learning for Multi-party Decision Making

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Friday, October 28, 2022 - Saturday, October 29, 2022
8:30 AM - 3:30 PM
Type: Workshops
Organizer(s): Segev Wasserkrug | David Pennock | Tamra Carpenter
Many real world decision making situations involve the decisions of multiple parties Typically in such situations each party wants to optimize its own objectives even knowing that their actions affect the objectives of others and vice versa Game theory is the mathematical science intended to model such situations Yet many
Oct 27 2022

Enumerative Combinatorics and Coding Theory

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Thursday, October 27, 2022
5:00 PM - 6:00 PM
Type: Seminars | Experimental Math Seminar
Presenter(s): Ilias Kotsireas - Wilfrid Laurier University
Subtitle: Eliahou Theory and application to enumerating Legendre Pairs In his seminal 1994 paper entitled "Enumerative combinatorics and coding theory", Shalom Eliahou proposes a theory/method to enumerate the values of
Oct 26 2022

Random Restrictions on Boolean Functions with Small Influences

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Wednesday, October 26, 2022
11:00 AM - 12:15 PM
Type: Seminars | Theoretical Computer Science Seminar
Presenter(s): Pei Wu - Institute for Advanced Study
In the talk, we discuss the probability of Boolean functions with small max influence to become constant under random restrictions. Let f be a Boolean function such that the variance
Oct 26 2022

Spectral Telescope: Convergence Rate Bounds for Random- Scan Gibbs Samplers Based on a Hierarchical Structure

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Wednesday, October 26, 2022
11:50 AM - 12:50 PM
Type: Seminars | DATA-INSPIRE TRIPODS Seminars
Presenter(s): Qian Qin - University of Minnesota
In this talk, we describe a simple but intriguing hierarchical structure found in random-scan Gibbs samplers, or Glauber dynamics. This structure connects Gibbs samplers targeting higher dimensional distributions to Gibbs
Oct 26 2022

Skeletons and Shadows (of polytopes)

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Wednesday, October 26, 2022
12:15 PM - 1:15 PM
Type: Seminars | Graduate Combinatorics Seminar
Presenter(s): Caleb Fong - Rutgers University
Steinitz's theorem gives a neat characterisation for the graphs (1-skeleta) of 3-dimensional convex polytopes. In this talk, I will sketch one direction of the proof (using shadows), and give a
Oct 24 2022

Log-concavity and Cross Product Conjecture in Order Theory

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Monday, October 24, 2022
2:00 PM - 3:00 PM
Type: Seminars | Rutgers Discrete Mathematics Seminar
Presenter(s): Swee Hong Chan - Rutgers University
The study of log-concave inequalities has played a central role in the study of the order theory. One such inequality is Stanley's inequality, which asserts the log-concavity of the sequence
Oct 21 2022

Learning-Based Robot Control from Vision: Formal Guarantees and Fundamental Limits

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Friday, October 21, 2022
10:00 AM - 11:00 AM
Type: Seminars | DATA-INSPIRE TRIPODS Seminars
Presenter(s): Anirudha Majumdar - Princeton University
The ability of machine learning techniques to process rich sensory inputs such as vision makes them highly appealing for use in robotic systems (e.g., micro aerial vehicles and robotic manipulators).
Oct 19 2022

Cut Query Algorithms Using Star Contraction

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Wednesday, October 19, 2022
11:00 AM - 12:15 PM
Type: Seminars | Theoretical Computer Science Seminar
Presenter(s): Yuval Efron - Columbia University
In this talk I'll discuss a simple combinatorial randomized procedure, which is styled Star Contraction. Then, I'll discuss applications of this technical procedure, with the central one being a randomized
Oct 19 2022

Using the Borsuk-Ulam Theorem to Prove the Chromatic Number of the Knaser Graph

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Wednesday, October 19, 2022
12:15 PM - 1:15 PM
Type: Seminars | Graduate Combinatorics Seminar
Presenter(s): Nilava Metya - Rutgers University
The Knaser graph K(n,k) is the graph whose vertices are the n-subsets of {1,2,..,2n+k} and two vertices are connected if and only if they don't intersect. An example is the
Oct 19 2022

Counter Examples for Stochastic Gradient Descent

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Wednesday, October 19, 2022
11:50 AM - 12:50 PM
Type: Seminars | DATA-INSPIRE TRIPODS Seminars
Presenter(s): Vivak Patel - University of Wisconsin, Madison
Stochastic Gradient Descent (SGD) is a widely deployed algorithm for solving estimation problems that arise in statistics and learning. Accordingly, SGD has been analyzed from many perspectives to understand its