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We consider an online vector balancing question where $T$ vectors, chosen from an arbitrary distribution over $[-1,1]^n$, arrive one-by-one and must be immediately given a $\pm$ sign. The goal is to keep the discrepancy small as possible. A…

Data Structures and Algorithms · Computer Science 2020-04-14 Nikhil Bansal , Haotian Jiang , Sahil Singla , Makrand Sinha

We study the online discrepancy minimization problem for vectors in $\mathbb{R}^d$ in the oblivious setting where an adversary is allowed fix the vectors $x_1, x_2, \ldots, x_n$ in arbitrary order ahead of time. We give an algorithm that…

Data Structures and Algorithms · Computer Science 2021-02-09 David Arbour , Drew Dimmery , Tung Mai , Anup Rao

In the stochastic online vector balancing problem, vectors $v_1,v_2,\ldots,v_T$ chosen independently from an arbitrary distribution in $\mathbb{R}^n$ arrive one-by-one and must be immediately given a $\pm$ sign. The goal is to keep the norm…

Data Structures and Algorithms · Computer Science 2020-07-22 Nikhil Bansal , Haotian Jiang , Raghu Meka , Sahil Singla , Makrand Sinha

We prove that there exists an online algorithm that for any sequence of vectors $v_1,\ldots,v_T \in \mathbb{R}^n$ with $\|v_i\|_2 \leq 1$, arriving one at a time, decides random signs $x_1,\ldots,x_T \in \{ -1,1\}$ so that for every $t \le…

Data Structures and Algorithms · Computer Science 2023-08-04 Janardhan Kulkarni , Victor Reis , Thomas Rothvoss

We consider the online vector bin packing problem where $n$ items specified by $d$-dimensional vectors must be packed in the fewest number of identical $d$-dimensional bins. Azar et al. (STOC'13) showed that for any online algorithm $A$,…

Data Structures and Algorithms · Computer Science 2020-08-06 Nikhil Bansal , Ilan Reuven Cohen

Online load balancing for heterogeneous machines aims to minimize the makespan (maximum machine workload) by scheduling arriving jobs with varying sizes on different machines. In the adversarial setting, where an adversary chooses not only…

Data Structures and Algorithms · Computer Science 2024-05-22 Sungjin Im , Ravi Kumar , Shi Li , Aditya Petety , Manish Purohit

We study the minimum-cost metric perfect matching problem under online i.i.d arrivals. We are given a fixed metric with a server at each of the points, and then requests arrive online, each drawn independently from a known probability…

Data Structures and Algorithms · Computer Science 2019-04-22 Anupam Gupta , Guru Guruganesh , Binghui Peng , David Wajc

We study the operator norm discrepancy of i.i.d. random matrices, initiating the matrix-valued analog of a long line of work on the $\ell^{\infty}$ norm discrepancy of i.i.d. random vectors. First, using repurposed results on vector…

Data Structures and Algorithms · Computer Science 2024-07-23 Dmitriy Kunisky , Peiyuan Zhang

We study an online vector balancing problem, in which $n$ independent Gaussian random vectors $\boldsymbol{\zeta}(1),\dots,\boldsymbol{\zeta}(n) \sim \mathcal{N}(0, I_n)$, each of dimension $n$, arrive one at a time. The goal is to choose…

Probability · Mathematics 2026-05-15 Christian Fiedler , Joe Jackson , Daniel Lacker , Jonathan Niles-Weed

The vector-balancing problem is a fundamental problem in discrepancy theory: given T vectors in $[-1,1]^n$, find a signing $\sigma(a) \in \{\pm 1\}$ of each vector $a$ to minimize the discrepancy $\| \sum_{a} \sigma(a) \cdot a \|_{\infty}$.…

Data Structures and Algorithms · Computer Science 2021-11-12 Anupam Gupta , Vijaykrishna Gurunathan , Ravishankar Krishnaswamy , Amit Kumar , Sahil Singla

Modern data centers face a key challenge of effectively serving user requests that arrive online. Such requests are inherently multi-dimensional and characterized by demand vectors over multiple resources such as processor cycles, storage…

Data Structures and Algorithms · Computer Science 2015-08-19 Sungjin Im , Nathaniel Kell , Janardhan Kulkarni , Debmalya Panigrahi

In the online sorting problem, we have an array $A$ of $n$ cells, and receive a stream of $n$ items $x_1,\dots,x_n\in [0,1]$. When an item arrives, we need to immediately and irrevocably place it into an empty cell. The goal is to minimize…

Data Structures and Algorithms · Computer Science 2025-10-23 Yang Hu

We consider the discrepancy problem of coloring $n$ intervals with $k$ colors such that at each point on the line, the maximal difference between the number of intervals of any two colors is minimal. Somewhat surprisingly, a coloring with…

Data Structures and Algorithms · Computer Science 2010-12-20 Antonios Antoniadis , Falk Hüffner , Pascal Lenzner , Carsten Moldenhauer , Alexander Souza

In the classic online graph balancing problem, edges arrive sequentially and must be oriented immediately upon arrival, to minimize the maximum in-degree. For adversarial arrivals, the natural greedy algorithm is $O(\log n)$-competitive,…

Data Structures and Algorithms · Computer Science 2026-04-07 Nikhil Bansal , Milind Prabhu , Sahil Singla , Siddharth M. Sundaram

In the Maximum Independent Set of Hyperrectangles problem, we are given a set of $n$ (possibly overlapping) $d$-dimensional axis-aligned hyperrectangles, and the goal is to find a subset of non-overlapping hyperrectangles of maximum…

Data Structures and Algorithms · Computer Science 2024-06-28 Mohit Garg , Debajyoti Kar , Arindam Khan

In the online matching on the line problem, the task is to match a set of requests $R$ online to a given set of servers $S$. The distance metric between any two points in $R\,\cup\, S$ is a line metric and the objective for the online…

Data Structures and Algorithms · Computer Science 2017-12-20 Antonios Antoniadis , Carsten Fischer , Andreas Tönnis

We consider the online carpooling problem: given $n$ vertices, a sequence of edges arrive over time. When an edge $e_t = (u_t, v_t)$ arrives at time step $t$, the algorithm must orient the edge either as $v_t \rightarrow u_t$ or $u_t…

Data Structures and Algorithms · Computer Science 2020-10-06 Anupam Gupta , Ravishankar Krishnaswamy , Amit Kumar , Sahil Singla

Consider an infinite sequence of independent, uniformly chosen points from $[0,1]^d$. After looking at each point in the sequence, an overseer is allowed to either keep it or reject it, and this choice may depend on the locations of all…

Probability · Mathematics 2017-09-05 Raaz Dwivedi , Ohad N. Feldheim , Ori Gurel-Gurevich , Aaditya Ramdas

For online matching with the line metric, we present a lower bound of $\Omega(\log n)$ on the approximation ratio of any online (possibly randomized) algorithm. This beats the previous best lower bound of $\Omega(\sqrt{\log n})$ and matches…

Data Structures and Algorithms · Computer Science 2021-08-23 Kangning Wang

We study the matrix discrepancy problem in the average-case setting. Given a sequence of $m \times m$ symmetric matrices $A_1,\ldots,A_n$, its discrepancy is defined as the minimal spectral norm over all signed sums $\sum_{i=1}^n x_iA_i$…

Probability · Mathematics 2025-10-07 Dmitriy Kunisky , Timm Oertel , Nicola Wengiel , Peiyuan Zhang
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